Development of Gridded Fields of Urban Canopy Parameters for Advanced Urban Meteorological and Air Quality Models

EPA Science Inventory

Urban dispersion and air quality simulation models applied at various horizontal scales require different levels of fidelity for specifying the characteristics of the underlying surfaces. As the modeling scales approach the neighborhood level (~1 km horizontal grid spacing), the...

Urban Modification of Convection and Rainfall in Complex Terrain

NASA Astrophysics Data System (ADS)

Freitag, B. M.; Nair, U. S.; Niyogi, D.

2018-03-01

Despite a globally growing proportion of cities located in regions of complex terrain, interactions between urbanization and complex terrain and their meteorological impacts are not well understood. We utilize numerical model simulations and satellite data products to investigate such impacts over San Miguel de Tucumán, Argentina. Numerical modeling experiments show urbanization results in 20-30% less precipitation downwind of the city and an eastward shift in precipitation upwind. Our experiments show that changes in surface energy, boundary layer dynamics, and thermodynamics induced by urbanization interact synergistically with the persistent forcing of atmospheric flow by complex terrain. With urbanization increasing in mountainous regions, land-atmosphere feedbacks can exaggerate meteorological forcings leading to weather impacts that require important considerations for sustainable development of urban regions within complex terrain.

AN INTERDISCIPLINARY APPROACH TO ADDRESSING NEIGHBORHOOD SCALE AIR QUALITY CONCERNS: THE INTEGRATION OF GIS, URBAN MORPHOLOGY, PREDICTIVE METEOROLOGY, AND AIR QUALITY MONITORING TOOLS

EPA Science Inventory

The paper describes a project that combines the capabilities of urban geography, raster-based GIS, predictive meteorological and air pollutant diffusion modeling, to support a neighborhood-scale air quality monitoring pilot study under the U.S. EPA EMPACT Program. The study ha...

Evaluation of urban surface parameterizations in the WRF model using measurements during the Texas Air Quality Study 2006 field campaign

NASA Astrophysics Data System (ADS)

Lee, S.-H.; Kim, S.-W.; Angevine, W. M.; Bianco, L.; McKeen, S. A.; Senff, C. J.; Trainer, M.; Tucker, S. C.; Zamora, R. J.

2010-10-01

The impact of urban surface parameterizations in the WRF (Weather Research and Forecasting) model on the simulation of local meteorological fields is investigated. The Noah land surface model (LSM), a modified LSM, and a single-layer urban canopy model (UCM) have been compared, focusing on urban patches. The model simulations were performed for 6 days from 12 August to 17 August during the Texas Air Quality Study 2006 field campaign. Analysis was focused on the Houston-Galveston metropolitan area. The model simulated temperature, wind, and atmospheric boundary layer (ABL) height were compared with observations from surface meteorological stations (Continuous Ambient Monitoring Stations, CAMS), wind profilers, the NOAA Twin Otter aircraft, and the NOAA Research Vessel Ronald H. Brown. The UCM simulation showed better results in the comparison of ABL height and surface temperature than the LSM simulations, whereas the original LSM overestimated both the surface temperature and ABL height significantly in urban areas. The modified LSM, which activates hydrological processes associated with urban vegetation mainly through transpiration, slightly reduced warm and high biases in surface temperature and ABL height. A comparison of surface energy balance fluxes in an urban area indicated the UCM reproduces a realistic partitioning of sensible heat and latent heat fluxes, consequently improving the simulation of urban boundary layer. However, the LSMs have a higher Bowen ratio than the observation due to significant suppression of latent heat flux. The comparison results suggest that the subgrid heterogeneity by urban vegetation and urban morphological characteristics should be taken into account along with the associated physical parameterizations for accurate simulation of urban boundary layer if the region of interest has a large fraction of vegetation within the urban patch. Model showed significant discrepancies in the specific meteorological conditions when nocturnal low-level jets exist and a thermal internal boundary layer over water forms.

The Application of Satellite-Derived, High-Resolution Land Use/Land Cover Data to Improve Urban Air Quality Model Forecasts

NASA Technical Reports Server (NTRS)

Quattrochi, D. A.; Lapenta, W. M.; Crosson, W. L.; Estes, M. G., Jr.; Limaye, A.; Kahn, M.

2006-01-01

Local and state agencies are responsible for developing state implementation plans to meet National Ambient Air Quality Standards. Numerical models used for this purpose simulate the transport and transformation of criteria pollutants and their precursors. The specification of land use/land cover (LULC) plays an important role in controlling modeled surface meteorology and emissions. NASA researchers have worked with partners and Atlanta stakeholders to incorporate an improved high-resolution LULC dataset for the Atlanta area within their modeling system and to assess meteorological and air quality impacts of Urban Heat Island (UHI) mitigation strategies. The new LULC dataset provides a more accurate representation of land use, has the potential to improve model accuracy, and facilitates prediction of LULC changes. Use of the new LULC dataset for two summertime episodes improved meteorological forecasts, with an existing daytime cold bias of approx. equal to 3 C reduced by 30%. Model performance for ozone prediction did not show improvement. In addition, LULC changes due to Atlanta area urbanization were predicted through 2030, for which model simulations predict higher urban air temperatures. The incorporation of UHI mitigation strategies partially offset this warming trend. The data and modeling methods used are generally applicable to other U.S. cities.

Satellite data based approach for the estimation of anthropogenic heat flux over urban areas

NASA Astrophysics Data System (ADS)

Nitis, Theodoros; Tsegas, George; Moussiopoulos, Nicolas; Gounaridis, Dimitrios; Bliziotis, Dimitrios

2017-09-01

Anthropogenic effects in urban areas influence the thermal conditions in the environment and cause an increase of the atmospheric temperature. The cities are sources of heat and pollution, affecting the thermal structure of the atmosphere above them which results to the urban heat island effect. In order to analyze the urban heat island mechanism, it is important to estimate the anthropogenic heat flux which has a considerable impact on the urban energy budget. The anthropogenic heat flux is the result of man-made activities (i.e. traffic, industrial processes, heating/cooling) and thermal releases from the human body. Many studies have underlined the importance of the Anthropogenic Heat Flux to the calculation of the urban energy budget and subsequently, the estimation of mesoscale meteorological fields over urban areas. Therefore, spatially disaggregated anthropogenic heat flux data, at local and city scales, are of major importance for mesoscale meteorological models. The main objectives of the present work are to improve the quality of such data used as input for mesoscale meteorological models simulations and to enhance the application potential of GIS and remote sensing in the fields of climatology and meteorology. For this reason, the Urban Energy Budget concept is proposed as the foundation for an accurate determination of the anthropogenic heat discharge as a residual term in the surface energy balance. The methodology is applied to the cities of Athens and Paris using the Landsat ETM+ remote sensing data. The results will help to improve our knowledge on Anthropogenic Heat Flux, while the potential for further improvement of the methodology is also discussed.

National Urban Database and Access Portal Tool

EPA Science Inventory

Based on the need for advanced treatments of high resolution urban morphological features (e.g., buildings, trees) in meteorological, dispersion, air quality and human exposure modeling systems for future urban applications, a new project was launched called the National Urban Da...

Meteorological and air pollution modeling for an urban airport

NASA Technical Reports Server (NTRS)

Swan, P. R.; Lee, I. Y.

1980-01-01

Results are presented of numerical experiments modeling meteorology, multiple pollutant sources, and nonlinear photochemical reactions for the case of an airport in a large urban area with complex terrain. A planetary boundary-layer model which predicts the mixing depth and generates wind, moisture, and temperature fields was used; it utilizes only surface and synoptic boundary conditions as input data. A version of the Hecht-Seinfeld-Dodge chemical kinetics model is integrated with a new, rapid numerical technique; both the San Francisco Bay Area Air Quality Management District source inventory and the San Jose Airport aircraft inventory are utilized. The air quality model results are presented in contour plots; the combined results illustrate that the highly nonlinear interactions which are present require that the chemistry and meteorology be considered simultaneously to make a valid assessment of the effects of individual sources on regional air quality.

Meteorological and air quality impacts of increased urban albedo and vegetative cover in the Greater Toronto Area, Canada

DOE Office of Scientific and Technical Information (OSTI.GOV)

Taha, Haider; Hammer, Hillel; Akbari, Hashem

2002-04-30

The study described in this report is part of a project sponsored by the Toronto Atmospheric Fund, performed at the Lawrence Berkeley National Laboratory, to assess the potential role of surface property modifications on energy, meteorology, and air quality in the Greater Toronto Area (GTA), Canada. Numerical models were used to establish the possible meteorological and ozone air-quality impacts of increased urban albedo and vegetative fraction, i.e., ''cool-city'' strategies that can mitigate the urban heat island (UHI), significantly reduce urban energy consumption, and improve thermal comfort, particularly during periods of hot weather in summer. Mitigation is even more important duringmore » critical heat wave periods with possible increased heat-related hospitalization and mortality. The evidence suggests that on an annual basis cool-city strategies are beneficial, and the implementation of such measures is currently being investigated in the U.S. and Canada. We simulated possible scenari os for urban heat-island mitigation in the GTA and investigated consequent meteorological changes, and also performed limited air-quality analysis to assess related impacts. The study was based on a combination of mesoscale meteorological modeling, Lagrangian (trajectory), and photochemical trajectory modeling to assess the potential meteorological and ozone air-quality impacts of cool-city strategies. As available air-quality and emissions data are incompatible with models currently in use at LBNL, our air-quality analysis was based on photochemical trajectory modeling. Because of questions as to the accuracy and appropriateness of this approach, in our opinion this aspect of the study can be improved in the future, and the air-quality results discussed in this report should be viewed as relatively qualitative. The MM5 meteorological model predicts a UHI in the order of 2 to 3 degrees C in locations of maxima, and about 1 degree C as a typical value over most of the urban area. Our si mulations suggest that cool-city strategies can typically reduce local urban air temperature by 0.5-1 degrees C; as more sporadic events, larger decreases (1.5 degrees C, 2.5-2.7 degrees C and 4-6 degrees C) were also simulated. With regard to ozone mixing ratios along the simulated trajectories, the effects of cool-city strategies appear to be on the order of 2 ppb, a typical decrease. The photochemical trajectory model (CIT) also simulates larger decreases (e.g., 4 to 8 ppb), but these are not taken as representative of the potential impacts in this report. A comparison with other simulations suggest very crudely that a decrease of this magnitude corresponds to significant ''equivalent'' decreases in both NOx and VOCs emissions in the region. Our preliminary results suggest that significant UHI control can be achieved with cool-cities strategies in the GTA and is therefore worth further study. We recommend that better input data and more accurate modeling schemes be used to carry out f uture studies in the same direction.« less

An Urban Diffusion Simulation Model for Carbon Monoxide

ERIC Educational Resources Information Center

Johnson, W. B.; And Others

1973-01-01

A relatively simple Gaussian-type diffusion simulation model for calculating urban carbon (CO) concentrations as a function of local meteorology and the distribution of traffic is described. The model can be used in two ways: in the synoptic mode and in the climatological mode. (Author/BL)

REVIEW OF THE ATTRIBUTES AND PERFORMANCE OF SIX URBAN DIFFUSION MODELS

EPA Science Inventory

The American Meteorological Society conducted a scientific review of a set of six urban diffusion models. TRC Environmental Consultants, Inc. calculated and tabulated a uniform set of statistics for all the models. The report consists of a summary and copies of the three independ...

Modelling NOX concentrations through CFD-RANS in an urban hot-spot using high resolution traffic emissions and meteorology from a mesoscale model

NASA Astrophysics Data System (ADS)

Sanchez, Beatriz; Santiago, Jose Luis; Martilli, Alberto; Martin, Fernando; Borge, Rafael; Quaassdorff, Christina; de la Paz, David

2017-08-01

Air quality management requires more detailed studies about air pollution at urban and local scale over long periods of time. This work focuses on obtaining the spatial distribution of NOx concentration averaged over several days in a heavily trafficked urban area in Madrid (Spain) using a computational fluid dynamics (CFD) model. A methodology based on weighted average of CFD simulations is applied computing the time evolution of NOx dispersion as a sequence of steady-state scenarios taking into account the actual atmospheric conditions. The inputs of emissions are estimated from the traffic emission model and the meteorological information used is derived from a mesoscale model. Finally, the computed concentration map correlates well with 72 passive samplers deployed in the research area. This work reveals the potential of using urban mesoscale simulations together with detailed traffic emissions so as to provide accurate maps of pollutant concentration at microscale using CFD simulations.

COST 728 Project Report: Urbanization of Meteorological and Air Quality Models - Chapter 5 - Model Urbanization Strategy: Summaries, Recommendations and Requirements

EPA Science Inventory

The urban canopy (UC), the layer of the atmosphere between the ground and the top of the highest buildings, is the region where people live and human activities take place. Because of this importance (e.g., human health, preservation of buildings) significant efforts have been d...

Developing of the database of meteorological and radiation fields for Moscow region (urban reanalysis) for 1981-2014 period with high spatial and temporal resolution. Strategy and first results.

NASA Astrophysics Data System (ADS)

Konstantinov, Pavel; Varentsov, Mikhail; Platonov, Vladimir; Samsonov, Timofey; Zhdanova, Ekaterina; Chubarova, Natalia

2017-04-01

The main goal of this investigation is to develop a kind of "urban reanalysis" - the database of meteorological and radiation fields under Moscow megalopolis for period 1981-2014 with high spatial resolution. Main meteorological fields for Moscow region are reproduced with COSMO_CLM regional model (including urban parameters) with horizontal resolution 1x1 km. Time resolution of output fields is 1 hour. For radiation fields is quite useful to calculate SVF (Sky View Factor) for obtaining losses of UV radiation in complex urban conditions. Usually, the raster-based SVF analysis the shadow-casting algorithm proposed by Richens (1997) is popular (see Ratti and Richens 2004, Gal et al. 2008, for example). SVF image is obtained by combining shadow images obtained from different directions. An alternative is to use raster-based SVF calculation similar to vector approach using digital elevation model of urban relief. Output radiation field includes UV-radiation with horizontal resolution 1x1 km This study was financially supported by the Russian Foundation for Basic Research within the framework of the scientific project no. 15-35-21129 _mol_a_ved and project no 15-35-70006 mol_a_mos References: 1. Gal, T., Lindberg, F., and Unger, J., 2008. Computing continuous sky view factors using 3D urban raster and vector databases: comparison and application to urban climate. Theoretical and applied climatology, 95 (1-2), 111-123. 2. Richens, P., 1997. Image processing for urban scale environmental modelling. In: J.D. Spitler and J.L.M. Hensen, eds. th Intemational IBPSA Conference Building Simulation, Prague. 3. Ratti, C. and Richens, P., 2004. Raster analysis of urban form. Environment and Planning B: Planning and Design, 31 (2), 297-309.

Air pollution removal by urban trees and shrubs in the United States

Treesearch

David J. Nowak; Daniel E. Crane; Jack C. Stevens

2006-01-01

A modeling study using hourly meteorological and pollution concentration data from across the coterminous United States demonstrates that urban trees remove large amounts of air pollution that consequently improve urban air quality. Pollution removal (03, PM10, NO2, SO2, CO)...

Enviro-HIRLAM in Studies of Urban and Aerosol Impacts on Metropolitan Areas: Science-Education Approach

NASA Astrophysics Data System (ADS)

Mahura, Alexander; Nuterman, Roman; Mazeikis, Adomas; Gonzalez-Aparicio, Iratxe; Ivanov, Sergey; Palamarchuk, Julia

2014-05-01

To attract more perspective young scientists (and especially, MSc and PhD students) for advanced research and development of complex and modern modelling systems, a specific approach is required. It should allow within a short period of time to evaluate personal background levels, skills, capabilities, etc. To learn more about new potential science-oriented developers of the models, it is often not enough to look into the personal resume. Thus, a special event such as Young Scientist Summer School (YSSS) can be organized, where young researchers could have an opportunity to attend not only relevant lectures, but also participate in practical exercises allowing to solidify lecture materials. Here, the practical exercises are presented as independent small-scale (having duration of up to a week) research projects or studies oriented on specific topics of YSSS. Developed approach was tested and realized during 2008 and 2011 YSSS events held and organized in Zelenogorsk, Russia (by NetFAM et al.; http://netfam.fmi.fi/YSSS08) and Odessa, Ukraine (by MUSCATEN et al.; http://atmos.physic.ut.ee/~muscaten/YSSS/1info.html), respectively. It has been refined for the new YSSS (Jul 2014) to be organized by the COST Action EuMetChem. The main focus of all these YSSSs was/is on the integrated modelling of meteorological and chemical transport processes and impact of chemical weather on numerical weather prediction and climate modelling. During previous YSSSs some of such projects - "URBAN: The Influence of Metropolitan Areas on Meteorology", "AEROSOL: The Impact of Aerosols Effects on Meteorology", and "COASTAL: The Coastal & Cities Effects on Meteorology" - were focused on evaluation of influence of metropolitan areas on formation of meteorological and chemical fields above urban areas (such as Paris, France; Copenhagen, Denmark, and Bilbao, Spain) and surroundings. The Environment - HIgh Resolution Limited Area Model (Enviro-HIRLAM) was used and modifications were made taking into account urban (anthropogenic heat flux, roughness, buildings and their characteristics), chemical species/ aerosol (feedback mechanisms) effects with further analysis of temporal and spatial variability of diurnal cycle for meteorological variables of key importance. Main items of listed above YSSS small-scale research projects include the following: • Introduction with background discussions (with brainstorming to outline research and technical tasks planned including main goal, specific objectives, etc.) in groups; • Analysis of meteorological situations (selecting specific cases/ dates using surface maps, diagrams of vertical sounding, and surface meteorological measurements); • Learning practical technical steps (in order to make necessary changes in the model and implementing urban and aerosol effects, compiling executables, making test runs); • Performing model runs/simulations at different options (dates, control vs. modified urban and aerosol runs, forecast lengths, spatial and temporal resolutions, etc.); • Visualization/ plotting of results obtained (in a form of graphs, tables, animations); • Evaluation of possible impact on urban areas (estimating differences between the control and modified runs through temporal and spatial variability of simulated meteorological (air temperature, wind speed, relative humidity, sensible and latent heat fluxes, etc.) and chemical pollutants (concentration and deposition) fields/ patterns; • Team's oral presentation of the project about results and findings and following guidelines (including aim and specific objectives, methodology and approaches, results and discussions with examples, conclusions, acknowledgements, references). Outline and detailed description of the developed approach, key items of the research projects and their schedules, preparatory steps including team of students' familiarization with general information on planned exercises and literature list (composed of required, recommended, and additional readings), requirements for successful completion and defense of the project, team independent work as well as under supervision are presented and discussed.

Evaluation of data assimilation techniques for a mesoscale meteorological model and their effects on air quality model results

NASA Astrophysics Data System (ADS)

Amicarelli, A.; Gariazzo, C.; Finardi, S.; Pelliccioni, A.; Silibello, C.

2008-05-01

Data assimilation techniques are methods to limit the growth of errors in a dynamical model by allowing observations distributed in space and time to force (nudge) model solutions. They have become common for meteorological model applications in recent years, especially to enhance weather forecast and to support air-quality studies. In order to investigate the influence of different data assimilation techniques on the meteorological fields produced by RAMS model, and to evaluate their effects on the ozone and PM10 concentrations predicted by FARM model, several numeric experiments were conducted over the urban area of Rome, Italy, during a summer episode.

NATIONAL URBAN DATABASE AND ACCESS PORTAL TOOL (NUDAPT): FACILITATING ADVANCEMENTS IN URBAN METEOROLOGY AND CLIMATE MODELING WITH COMMUNITY-BASED URBAN DATABASES

EPA Science Inventory

We discuss the initial design and application of the National Urban Database and Access Portal Tool (NUDAPT). This new project is sponsored by the USEPA and involves collaborations and contributions from many groups from federal and state agencies, and from private and academic i...

Improvement of Advanced Storm-scale Analysis and Prediction System (ASAPS) on Seoul Metropolitan Area, Korea

NASA Astrophysics Data System (ADS)

Park, Jeong-Gyun; Jee, Joon-Bum

2017-04-01

Dangerous weather such as severe rain, heavy snow, drought and heat wave caused by climate change make more damage in the urban area that dense populated and industry areas. Urban areas, unlike the rural area, have big population and transportation, dense the buildings and fuel consumption. Anthropogenic factors such as road energy balance, the flow of air in the urban is unique meteorological phenomena. However several researches are in process about prediction of urban meteorology. ASAPS (Advanced Storm-scale Analysis and Prediction System) predicts a severe weather with very short range (prediction with 6 hour) and high resolution (every hour with time and 1 km with space) on Seoul metropolitan area based on KLAPS (Korea Local Analysis and Prediction System) from KMA (Korea Meteorological Administration). This system configured three parts that make a background field (SUF5), analysis field (SU01) with observation and forecast field with high resolution (SUF1). In this study, we improve a high-resolution ASAPS model and perform a sensitivity test for the rainfall case. The improvement of ASAPS include model domain configuration, high resolution topographic data and data assimilation with WISE observation data.

THE INFLUENCE OF A TALL BUILDING ON STREET-CANYON FLOW IN AN URBAN NEIGHBORHOOD

EPA Science Inventory

This study presents a velocity comparison between meteorological wind tunnel results and results from the Quick Urban & Industrial Complex model (QUIC, version 3.9) for a simplified urban area, representing a regular array of city blocks composed of row houses in Brooklyn, New Yo...

THE INFLUENCE OF A TALL BUILDING ON STREET CANYON FLOW IN AN URBAN NEIGBORHOOD

EPA Science Inventory

This study presents a velocity comparison between meteorological wind tunnel results and results from the Quick Urban & Industrial Complex model (QUIC, version 3.9) for a simplified urban area, representing a regular array of city blocks composed of row houses in Brooklyn, New Yo...

Application and evaluation of high-resolution WRF-CMAQ with simple urban parameterization.

EPA Science Inventory

The 2-way coupled WRF-CMAQ meteorology and air quality modeling system is evaluated for high-resolution applications by comparing to a regional air quality field study (Discover-AQ). The model was modified to better account for the effects of urban environments. High-resolution...

Application and evaluation of high-resolution WRF-CMAQ with simple urban parameterization

EPA Science Inventory

The 2-way coupled WRF-CMAQ meteorology and air quality modeling system is evaluated for high-resolution applications by comparing to a regional air quality field study (Discover-AQ). The model was modified to better account for the effects of urban environments. High-resolution...

60 years of UK visibility measurements: impact of meteorology and atmospheric pollutants on visibility

NASA Astrophysics Data System (ADS)

Singh, Ajit; Bloss, William J.; Pope, Francis D.

2017-02-01

Reduced visibility is an indicator of poor air quality. Moreover, degradation in visibility can be hazardous to human safety; for example, low visibility can lead to road, rail, sea and air accidents. In this paper, we explore the combined influence of atmospheric aerosol particle and gas characteristics, and meteorology, on long-term visibility. We use visibility data from eight meteorological stations, situated in the UK, which have been running since the 1950s. The site locations include urban, rural and marine environments. Most stations show a long-term trend of increasing visibility, which is indicative of reductions in air pollution, especially in urban areas. Additionally, the visibility at all sites shows a very clear dependence on relative humidity, indicating the importance of aerosol hygroscopicity on the ability of aerosol particles to scatter radiation. The dependence of visibility on other meteorological parameters, such as wind speed and wind direction, is also investigated. Most stations show long-term increases in temperature which can be ascribed to climate change, land-use changes (e.g. urban heat island effects) or a combination of both; the observed effect is greatest in urban areas. The impact of this temperature change upon local relative humidity is discussed. To explain the long-term visibility trends and their dependence on meteorological conditions, the measured data were fitted to a newly developed light-extinction model to generate predictions of historic aerosol and gas scattering and absorbing properties. In general, an excellent fit was achieved between measured and modelled visibility for all eight sites. The model incorporates parameterizations of aerosol hygroscopicity, particle concentration, particle scattering, and particle and gas absorption. This new model should be applicable and is easily transferrable to other data sets worldwide. Hence, historical visibility data can be used to assess trends in aerosol particle properties. This approach may help constrain global model simulations which attempt to generate aerosol fields for time periods when observational data are scarce or non-existent. Both the measured visibility and the modelled aerosol properties reported in this paper highlight the success of the UK's Clean Air Act, which was passed in 1956, in cleaning the atmosphere of visibility-reducing pollutants.

The blue skies in Beijing during APEC 2014: A quantitative assessment of emission control efficiency and meteorological influence

NASA Astrophysics Data System (ADS)

Liu, Hongli; He, Jing; Guo, Jianping; Miao, Yucong; Yin, Jinfang; Wang, Yuan; Xu, Hui; Liu, Huan; Yan, Yan; Li, Yuan; Zhai, Panmao

2017-10-01

Most previous studies attributed the alleviation of aerosol pollution to either emission control measures or favorable meteorological conditions. However, our understanding of their quantitative contribution is far from complete. In this study, based on model simulation using the CMA (China Meteorological Administration) Unified Atmospheric Chemistry Environment for aerosols (CUACE/Aero), in combination with simultaneous ground-based hourly PM2.5 observations, we aim to quantify the relative contributions of the emission control measures and meteorology to the blue-skies seen in Beijing during the Asia-Pacific Economic Cooperation (APEC) summit held in November of 2014. A series of model simulations have been performed over Beijing-Tianjin-Hebei (BTH) region by implementing nine different emission control schemes. To investigate the relative contributions of the emission control measures and meteorology, the study period has been divided into five episodes. Overall, the CUACE/Aero model can reasonably well reproduce the temporal and spatial evolution of PM2.5 during APEC 2014, although the model performance varies by different time periods and regions of interest. Model results show the emission control measures on average reduced the PM2.5 concentration by 41.3% in urban areas of Beijing and 39.7% in Huairou district, respectively, indicating emission control plays a significant role for the blue skies observed. Among all the emission control measures under investigation, local emission control in Beijing contributed the largest to the reduction of PM2.5 concentrations with a reduction of 35.5% in urban area of Beijing and 34.8% in Huairou, in contrast with the vehicle emission control in Hebei that contributed the least with a reduction of less than 1%. The emission control efficiency in five episodes has been assessed quantitatively, which falls in the range of 36.2%-41.2% in urban area of Beijing and 34.9%-40.7% in Huairou, indicative of no significant episode and geographic dependence in the emission control efficiency. The emission control measures and meteorology, however, alternated to dominate the absolute reduction of PM2.5 concentrations. When the weather conditions are unfavorable, emission control measures outperformed meteorology with a reduction of 55.3-59.4 μg/m3 in urban area of Beijing and 32.5-33 μg/m3 in Huairou. Conversely, when the northwesterly winds prevailed, meteorology tends to outweigh the role of emission control in accounting for the drop of PM2.5. The atmospheric dilution conditions are determined through the model calculation of the mass inflow of PM2.5 per unit volume near the surface. Our findings have significant implications for effective planning and implementation of emission control measures.

Estimating urban ground-level PM10 using MODIS 3km AOD product and meteorological parameters from WRF model

NASA Astrophysics Data System (ADS)

Ghotbi, Saba; Sotoudeheian, Saeed; Arhami, Mohammad

2016-09-01

Satellite remote sensing products of AOD from MODIS along with appropriate meteorological parameters were used to develop statistical models and estimate ground-level PM10. Most of previous studies obtained meteorological data from synoptic weather stations, with rather sparse spatial distribution, and used it along with 10 km AOD product to develop statistical models, applicable for PM variations in regional scale (resolution of ≥10 km). In the current study, meteorological parameters were simulated with 3 km resolution using WRF model and used along with the rather new 3 km AOD product (launched in 2014). The resulting PM statistical models were assessed for a polluted and largely variable urban area, Tehran, Iran. Despite the critical particulate pollution problem, very few PM studies were conducted in this area. The issue of rather poor direct PM-AOD associations existed, due to different factors such as variations in particles optical properties, in addition to bright background issue for satellite data, as the studied area located in the semi-arid areas of Middle East. Statistical approach of linear mixed effect (LME) was used, and three types of statistical models including single variable LME model (using AOD as independent variable) and multiple variables LME model by using meteorological data from two sources, WRF model and synoptic stations, were examined. Meteorological simulations were performed using a multiscale approach and creating an appropriate physic for the studied region, and the results showed rather good agreements with recordings of the synoptic stations. The single variable LME model was able to explain about 61%-73% of daily PM10 variations, reflecting a rather acceptable performance. Statistical models performance improved through using multivariable LME and incorporating meteorological data as auxiliary variables, particularly by using fine resolution outputs from WRF (R2 = 0.73-0.81). In addition, rather fine resolution for PM estimates was mapped for the studied city, and resulting concentration maps were consistent with PM recordings at the existing stations.

A study of model parameters associated with the urban climate using HCMM data. [analysis of St. Louis, Missouri infrared imagery

NASA Technical Reports Server (NTRS)

1981-01-01

Progress in the study of the intensity of the urban heat island is reported. The intensity of the heat island is commonly defined as the temperature difference between the center of the city and the surrounding suburban and rural regions. The intensity is considered as a function of changes in the season and changes in meteorological conditions in order to derive various parameters which may be used in numerical models for urban climate. Twelve case studies were selected and CCT's were ordered. In situ data was obtained from sixteen stations scattered about the city of St. Louis. Upper-air meteorological data were obtained and the water vapor and the temperature data were processed. Atmospheric transmissivities were computed for each of the case studies.

The model SIRANE for atmospheric urban pollutant dispersion. PART III: Validation against NO2 yearly concentration measurements in a large urban agglomeration

NASA Astrophysics Data System (ADS)

Soulhac, L.; Nguyen, C. V.; Volta, P.; Salizzoni, P.

2017-10-01

We present a validation study of an updated version of the SIRANE model, whose results have been systematically compared to concentrations of nitrogen dioxide collected over the whole urban agglomeration of Lyon. We model atmospheric dispersion of nitrogen oxides emitted by road traffic, industries and domestic heating. The meteorological wind field is computed by a pre-processor using data collected at a ground level monitoring station. Model results are compared with hourly concentrations measured at 15 monitoring stations over the whole year (2008). Further 75 passive diffusion samplers were used during 3 periods of 2 weeks to get a detailed spatial distribution over the west part of the city. An analysis of the model results depending on the variability of the meteorological input allows us to identify the causes for peculiar bad performances of the model and to identify possible improvements of the parameterisations implemented in it.

Urban Heat Islands and Their Mitigation vs. Local Impacts of Climate Change

NASA Astrophysics Data System (ADS)

Taha, H.

2007-12-01

Urban heat islands and their mitigation take on added significance, both negative and positive, when viewed from a climate-change perspective. In negative terms, urban heat islands can act as local exacerbating factors, or magnifying lenses, to the effects of regional and large-scale climate perturbations and change. They can locally impact meteorology, energy/electricity generation and use, thermal environment (comfort and heat waves), emissions of air pollutants, photochemistry, and air quality. In positive terms, on the other hand, mitigation of urban heat islands (via urban surface modifications and control of man-made heat, for example) can potentially have a beneficial effect of mitigating the local negative impacts of climate change. In addition, mitigation of urban heat islands can, in itself, contribute to preventing regional and global climate change, even if modestly, by helping reduce CO2 emissions from power plants and other sources as a result of decreased energy use for cooling (both direct and indirect) and reducing the rates of meteorology-dependent emissions of air pollutants. This presentation will highlight aspects and characteristics of heat islands, their mitigation, their modeling and quantification techniques, and recent advances in meso-urban modeling of California (funded by the California Energy Commission). In particular, the presentation will focus on results from quantitative, modeling-based analyses of the potential benefits of heat island mitigation in 1) reducing point- and area-source emissions of CO2, NOx, and VOC as a result of reduced cooling energy demand and ambient/surface temperatures, 2) reducing evaporative and fugitive hydrocarbon emissions as a result of lowered temperatures, 3) reducing biogenic hydrocarbon emissions from existing vegetative cover, 4) slowing the rates of tropospheric/ground-level ozone formation and/or accumulation in the urban boundary layer, and 5) helping improve air quality. Quantitative estimates of the above will be presented based on recent and earlier meteorological, energy, thermal environmental, emissions, and photochemical modeling studies for California and Texas.

Model analysis of urbanization impacts on boundary layer meteorology under hot weather conditions: a case study of Nanjing, China

NASA Astrophysics Data System (ADS)

Chen, Lei; Zhang, Meigen; Wang, Yongwei

2016-08-01

The Weather Research and Forecasting (WRF) model, configured with a single-layer urban canopy model, was employed to investigate the influence of urbanization on boundary layer meteorological parameters during a long-lasting heat wave. This study was conducted over Nanjing city, East China, from 26 July to 4 August 2010. The impacts of urban expansion and anthropogenic heat (AH) release were simulated to quantify their effects on 2-m temperature, 2-m water vapor mixing ratio, and 10-m wind speed and heat stress index. Urban sprawl increased the daily 2-m temperature in urbanized areas by around 1.6 °C and decreased the urban diurnal temperature range (DTR) by 1.24 °C. The contribution of AH release to the atmospheric warming was nearly 22 %, but AH had little influence on the DTR. The urban regional mean surface wind speed decreased by about 0.4 m s-1, and this decrease was successfully simulated from the surface to 300 m. The influence of urbanization on 2-m water vapor mixing ratio was significant over highly urbanized areas with a decrease of 1.1-1.8 g kg-1. With increased urbanization ratio, the duration of the inversion layer was about 4 h shorter, and the lower atmospheric layer was less stable. Urban heat island (UHI) intensity was significantly enhanced when synthesizing both urban sprawl and AH release and the daily mean UHI intensity increased by 0.74 °C. Urbanization increased the time under extreme heat stress (about 40 %) and worsened the living environment in urban areas.

Spatio-Temporal Change Modeling of Lulc: a Semantic Kriging Approach

NASA Astrophysics Data System (ADS)

Bhattacharjee, S.; Ghosh, S. K.

2015-07-01

Spatio-temporal land-use/ land-cover (LULC) change modeling is important to forecast the future LULC distribution, which may facilitate natural resource management, urban planning, etc. The spatio-temporal change in LULC trend often exhibits non-linear behavior, due to various dynamic factors, such as, human intervention (e.g., urbanization), environmental factors, etc. Hence, proper forecasting of LULC distribution should involve the study and trend modeling of historical data. Existing literatures have reported that the meteorological attributes (e.g., NDVI, LST, MSI), are semantically related to the terrain. Being influenced by the terrestrial dynamics, the temporal changes of these attributes depend on the LULC properties. Hence, incorporating meteorological knowledge into the temporal prediction process may help in developing an accurate forecasting model. This work attempts to study the change in inter-annual LULC pattern and the distribution of different meteorological attributes of a region in Kolkata (a metropolitan city in India) during the years 2000-2010 and forecast the future spread of LULC using semantic kriging (SemK) approach. A new variant of time-series SemK is proposed, namely Rev-SemKts to capture the multivariate semantic associations between different attributes. From empirical analysis, it may be observed that the augmentation of semantic knowledge in spatio-temporal modeling of meteorological attributes facilitate more precise forecasting of LULC pattern.

Remote Sensing of Urban Land Cover/Land Use Change, Surface Thermal Responses, and Potential Meteorological and Climate Change Impacts

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Jedlovec, Gary; Meyer, Paul

2011-01-01

City growth influences the development of the urban heat island (UHI), but the effect that local meteorology has on the UHI is less well known. This paper presents some preliminary findings from a study that uses multitemporal Landsat TM and ASTER data to evaluate land cover/land use change (LULCC) over the NASA Marshall Space Flight Center (MFSC) and its Huntsville, AL metropolitan area. Landsat NLCD data for 1992 and 2001 have been used to evaluate LULCC for MSFC and the surrounding urban area. Land surface temperature (LST) and emissivity derived from NLCD data have also been analyzed to assess changes in these parameters in relation to LULCC. Additionally, LULCC, LST, and emissivity have been identified from ASTER data from 2001 and 2011 to provide a comparison with the 2001 NLCD and as a measure of current conditions within the study area. As anticipated, the multi-temporal NLCD and ASTER data show that significant changes have occurred in land covers, LST, and emissivity within and around MSFC. The patterns and arrangement of these changes, however, is significant because the juxtaposition of urban land covers within and outside of MSFC provides insight on what impacts at a local to regional scale, the inter-linkage of these changes potentially have on meteorology. To further analyze these interactions between LULCC, LST, and emissivity with the lower atmosphere, a network of eleven weather stations has been established across the MSFC property. These weather stations provide data at a 10 minute interval, and these data are uplinked for use by MSFC facilities operations and the National Weather Service. The weather data are also integrated within a larger network of meteorological stations across north Alabama. Given that the MSFC weather stations will operate for an extended period of time, they can be used to evaluate how the building of new structures, and changes in roadways, and green spaces as identified in the MSFC master plan for the future, will potentially affect land cover LSTs across the Center. Moreover, the weather stations will also provide baseline data for developing a better understanding of how localized weather factors, such as extreme rainfall and heat events, affect micrometeorology. These data can also be used to model the interrelationships between LSTs and meteorology on a longer term basis to help evaluate how changes in these parameters can be quantified from satellite data collected in the future. In turn, the overall integration of multi-temporal meteorological information with LULCC, and LST data for MSFC proper and the surrounding Huntsville urbanized area can provide a perspective on how urban land surface types affect the meteorology in the boundary layer and ultimately, the UHI. Additionally, data such as this can be used as a foundation for modeling how climate change will potentially impact local and regional meteorology and conversely, how urban LULCC can or will influence changes on climate over the north Alabama area.

Development and application of a high resolution hybrid modelling system for the evaluation of urban air quality

NASA Astrophysics Data System (ADS)

Pepe, N.; Pirovano, G.; Lonati, G.; Balzarini, A.; Toppetti, A.; Riva, G. M.; Bedogni, M.

2016-09-01

A hybrid modelling system (HMS) was developed to provide hourly concentrations at the urban local scale. The system is based on the combination of a meteorological model (WRF), a chemical and transport eulerian model (CAMx), which computes concentration levels over the regional domains, and a lagrangian dispersion model (AUSTAL2000), accounting for dispersion phenomena within the urban area due to local emission sources; a source apportionment algorithm is also included in the HMS in order to avoid the double counting of local emissions. The HMS was applied over a set of nested domains, the innermost covering a 1.6 × 1.6 km2 area in Milan city center with 20 m grid resolution, for NOX simulation in 2010. For this paper the innermost domain was defined as ;local;, excluding usual definition of urban areas. WRF model captured the overall evolution of the main meteorological features, except for some very stagnant situations, thus influencing the subsequent performance of regional scale model CAMx. Indeed, CAMx was able to reproduce the spatial and temporal evolution of NOX concentration over the regional domain, except a few episodes, when observed concentrations were higher than 100 ppb. The local scale model AUSTAL2000 provided high-resolution concentration fields that sensibly mirrored the road and traffic pattern in the urban domain. Therefore, the first important outcome of the work is that the application of the hybrid modelling system allowed a thorough and consistent description of urban air quality. This result represents a relevant starting point for future evaluation of pollution exposure within an urban context. However, the overall performance of the HMS did not provide remarkable improvements with respect to stand-alone CAMx at the two only monitoring sites in Milan city center. HMS results were characterized by a smaller average bias, that improved about 6-8 ppb corresponding to 12-13% of the observed concentration, but by a lower correlation, that worsened around 1-3% (e.g. from 0.84 to 0.81 at Senato site), due to the concentration peaks produced by AUSTAL2000 during nighttime stable conditions. Additionally, the HMS results showed that it was unable to correctly take into account some local scale features (e.g. urban canyon effects), pointing out that the emission spatialization and time modulation criteria, especially those from road traffic, need further improvement. Nevertheless, a second important outcome of the work is that some of the most relevant discrepancies between modelled and observed concentrations were not related to the horizontal resolution of the dispersion models but to larger scale meteorological features not captured by the meteorological model, especially during winter period. Finally, the estimated contribution of the local emission sources accounted on the annual average for about 25-30% of the computed concentration levels in the innermost urban domain. This confirmed that the whole Milan urban area as well as the outside background areas, accounting all sources outside the innermost domain, play a key role on air quality. The result suggests that strictly local emission policies could have a limited and indecisive effect on urban air quality, although this finding could be partially biased by model underestimation of the observed concentration.

Enviro-HIRLAM online integrated meteorology-chemistry modelling system: strategy, methodology, developments and applications (v7.2)

NASA Astrophysics Data System (ADS)

Baklanov, Alexander; Smith Korsholm, Ulrik; Nuterman, Roman; Mahura, Alexander; Pagh Nielsen, Kristian; Hansen Sass, Bent; Rasmussen, Alix; Zakey, Ashraf; Kaas, Eigil; Kurganskiy, Alexander; Sørensen, Brian; González-Aparicio, Iratxe

2017-08-01

The Environment - High Resolution Limited Area Model (Enviro-HIRLAM) is developed as a fully online integrated numerical weather prediction (NWP) and atmospheric chemical transport (ACT) model for research and forecasting of joint meteorological, chemical and biological weather. The integrated modelling system is developed by the Danish Meteorological Institute (DMI) in collaboration with several European universities. It is the baseline system in the HIRLAM Chemical Branch and used in several countries and different applications. The development was initiated at DMI more than 15 years ago. The model is based on the HIRLAM NWP model with online integrated pollutant transport and dispersion, chemistry, aerosol dynamics, deposition and atmospheric composition feedbacks. To make the model suitable for chemical weather forecasting in urban areas, the meteorological part was improved by implementation of urban parameterisations. The dynamical core was improved by implementing a locally mass-conserving semi-Lagrangian numerical advection scheme, which improves forecast accuracy and model performance. The current version (7.2), in comparison with previous versions, has a more advanced and cost-efficient chemistry, aerosol multi-compound approach, aerosol feedbacks (direct and semi-direct) on radiation and (first and second indirect effects) on cloud microphysics. Since 2004, the Enviro-HIRLAM has been used for different studies, including operational pollen forecasting for Denmark since 2009 and operational forecasting atmospheric composition with downscaling for China since 2017. Following the main research and development strategy, further model developments will be extended towards the new NWP platform - HARMONIE. Different aspects of online coupling methodology, research strategy and possible applications of the modelling system, and fit-for-purpose model configurations for the meteorological and air quality communities are discussed.

NMOC, ozone, and organic aerosol in the southeastern United States, 1999-2007: 3. Origins of organic aerosol in Atlanta, Georgia, and surrounding areas

NASA Astrophysics Data System (ADS)

Blanchard, C. L.; Hidy, G. M.; Tanenbaum, S.; Edgerton, E. S.

2011-02-01

Carbonaceous compounds constitute a major fraction of the fine particle mass at locations throughout North America; much of the condensed-phase organic carbon (OC) is produced in the atmosphere from NMOC reactions as "secondary" OC (SOC). Ten years of particulate carbon and speciated non-methane organic compound (NMOC) data combined with other measurements from Southeastern Aerosol Research and Characterization (SEARCH) and other sites provide insight into the association between elemental carbon (EC), OC and NMOCs. Data are analyzed to characterize the OC and SOC contrasts between urban Atlanta, Georgia, and nearby non-urban conditions in the Southeast. Analysis of the monitoring record indicates that the mean Atlanta urban excess of total carbon (TC) is 2.1-2.8 μg m -3. The OC/EC ratio of the Atlanta urban excess is in the range 1.3 to 1.8, consistent with OC/EC ratios observed in motor vehicle emissions and a fossil carbon source of urban excess TC. Carbon isotope analysis of a subset of particle samples demonstrates that the urban excess is mainly fossil in origin, even though the majority of the TC is modern at both urban and non-urban sites. Temperature-dependent partitioning of OC between gas and condensed phases cannot explain the observed diurnal and seasonal variations of OC/CO, EC/CO, and OC/EC ratios. Alternatively, a hypothesis involving vertical mixing of OC-enriched air from aloft is supported by the seasonal and diurnal OC, isopentane, aromatic and isoprene observations at the ground. A statistical model is applied to indicate the relative significance of aerometric factors affecting OC and EC concentrations, including meteorological and pollutant associations. The model results demonstrate strong linkages between fine particle carbon and pollutant indicators of source emissions compared with meteorological factors; the model results show weaker dependence of OC on meteorological factors than is the case for ozone (O 3) concentrations.

Artificial neural network model for ozone concentration estimation and Monte Carlo analysis

NASA Astrophysics Data System (ADS)

Gao, Meng; Yin, Liting; Ning, Jicai

2018-07-01

Air pollution in urban atmosphere directly affects public-health; therefore, it is very essential to predict air pollutant concentrations. Air quality is a complex function of emissions, meteorology and topography, and artificial neural networks (ANNs) provide a sound framework for relating these variables. In this study, we investigated the feasibility of using ANN model with meteorological parameters as input variables to predict ozone concentration in the urban area of Jinan, a metropolis in Northern China. We firstly found that the architecture of network of neurons had little effect on the predicting capability of ANN model. A parsimonious ANN model with 6 routinely monitored meteorological parameters and one temporal covariate (the category of day, i.e. working day, legal holiday and regular weekend) as input variables was identified, where the 7 input variables were selected following the forward selection procedure. Compared with the benchmarking ANN model with 9 meteorological and photochemical parameters as input variables, the predicting capability of the parsimonious ANN model was acceptable. Its predicting capability was also verified in term of warming success ratio during the pollution episodes. Finally, uncertainty and sensitivity analysis were also performed based on Monte Carlo simulations (MCS). It was concluded that the ANN could properly predict the ambient ozone level. Maximum temperature, atmospheric pressure, sunshine duration and maximum wind speed were identified as the predominate input variables significantly influencing the prediction of ambient ozone concentrations.

ADVANCED URBANIZED METEOROLOGICAL MODELING AND AIR QUALITY SIMULATIONS WITH CMAQ AT NEIGHBORHOOD SCALES

EPA Science Inventory

We present results from a study testing the new boundary layer parameterization method, the canopy drag approach (DA) which is designed to explicitly simulate the effects of buildings, street and tree canopies on the dynamic, thermodynamic structure and dispersion fields in urban...

Detecting urban warming signals in climate records

NASA Astrophysics Data System (ADS)

He, Yuting; Jia, Gensuo; Hu, Yonghong; Zhou, Zijiang

2013-07-01

Determining whether air temperatures recorded at meteorological stations have been contaminated by the urbanization process is still a controversial issue at the global scale. With support of historical remote sensing data, this study examined the impacts of urban expansion on the trends of air temperature at 69 meteorological stations in Beijing, Tianjin, and Hebei Province over the last three decades. There were significant positive relations between the two factors at all stations. Stronger warming was detected at the meteorological stations that experienced greater urbanization, i.e., those with a higher urbanization rate. While the total urban area affects the absolute temperature values, the change of the urban area (urbanization rate) likely affects the temperature trend. Increases of approximately 10% in urban area around the meteorological stations likely contributed to the 0.13°C rise in air temperature records in addition to regional climate warming. This study also provides a new approach to selecting reference stations based on remotely sensed urban fractions. Generally, the urbanization-induced warming contributed to approximately 44.1% of the overall warming trends in the plain region of study area during the past 30 years, and the regional climate warming was 0.30°C (10 yr)-1 in the last three decades.

Urban Landscape Characterization Using Remote Sensing Data For Input into Air Quality Modeling

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Khan, Maudood

2005-01-01

The urban landscape is inherently complex and this complexity is not adequately captured in air quality models that are used to assess whether urban areas are in attainment of EPA air quality standards, particularly for ground level ozone. This inadequacy of air quality models to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well these models predict ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban growth projections as improved inputs to meteorological and air quality models focusing on the Atlanta, Georgia metropolitan area as a case study. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the Community Multiscale Air Quality (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1 km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality.

Enviro-HIRLAM/ HARMONIE Studies in ECMWF HPC EnviroAerosols Project

NASA Astrophysics Data System (ADS)

Hansen Sass, Bent; Mahura, Alexander; Nuterman, Roman; Baklanov, Alexander; Palamarchuk, Julia; Ivanov, Serguei; Pagh Nielsen, Kristian; Penenko, Alexey; Edvardsson, Nellie; Stysiak, Aleksander Andrzej; Bostanbekov, Kairat; Amstrup, Bjarne; Yang, Xiaohua; Ruban, Igor; Bergen Jensen, Marina; Penenko, Vladimir; Nurseitov, Daniyar; Zakarin, Edige

2017-04-01

The EnviroAerosols on ECMWF HPC project (2015-2017) "Enviro-HIRLAM/ HARMONIE model research and development for online integrated meteorology-chemistry-aerosols feedbacks and interactions in weather and atmospheric composition forecasting" is aimed at analysis of importance of the meteorology-chemistry/aerosols interactions and to provide a way for development of efficient techniques for on-line coupling of numerical weather prediction and atmospheric chemical transport via process-oriented parameterizations and feedback algorithms, which will improve both the numerical weather prediction and atmospheric composition forecasts. Two main application areas of the on-line integrated modelling are considered: (i) improved numerical weather prediction with short-term feedbacks of aerosols and chemistry on formation and development of meteorological variables, and (ii) improved atmospheric composition forecasting with on-line integrated meteorological forecast and two-way feedbacks between aerosols/chemistry and meteorology. During 2015-2016 several research projects were realized. At first, the study on "On-line Meteorology-Chemistry/Aerosols Modelling and Integration for Risk Assessment: Case Studies" focused on assessment of scenarios with accidental and continuous emissions of sulphur dioxide for case studies for Atyrau (Kazakhstan) near the northern part of the Caspian Sea and metallurgical enterprises on the Kola Peninsula (Russia), with GIS integration of modelling results into the RANDOM (Risk Assessment of Nature Detriment due to Oil spill Migration) system. At second, the studies on "The sensitivity of precipitation simulations to the soot aerosol presence" & "The precipitation forecast sensitivity to data assimilation on a very high resolution domain" focused on sensitivity and changes in precipitation life-cycle under black carbon polluted conditions over Scandinavia. At third, studies on "Aerosol effects over China investigated with a high resolution convection permitting weather model" & "Meteorological and chemical urban scale modelling for Shanghai metropolitan area" with focus on aerosol effects and influence of urban areas in China at regional-subregional-urban scales. At fourth, study on "Direct variational data assimilation algorithm for atmospheric chemistry data with transport and transformation model" with focus on testing chemical data assimilation algorithm of in situ concentration measurements on real data scenario. At firth, study on "Aerosol influence on High Resolution NWP HARMONIE Operational Forecasts" with focus on impact of sea salt aerosols on numerical weather prediction during low precipitation events. And finally, study on "Impact of regional afforestation on climatic conditions in metropolitan areas: case study of Copenhagen" with focus on impact of forest and land-cover change on formation and development of temperature regimes in the Copenhagen metropolitan area of Denmark. Selected results and findings will be presented and discussed.

Modeling of urban trees' effects on reducing human exposure to UV radiation in Seoul, Korea

Treesearch

Hang Ryeol Na; Gordon M. Heisler; David J. Nowak; Richard H. Grant

2014-01-01

A mathematical model isconstructed for quantifying urban trees’ effects on mitigating the intensity of ultraviolet (UV) radiation on the ground within different landuse types across a city. The model is based upon local field data, meteorological data and equations designed to predict the reduced UV fraction due to trees at the ground level. Trees in Seoul, Korea (2010...

THE NEW YORK MIDTOWN DISPERSION STUDY (MID-05) METEOROLOGICAL DATA REPORT.

DOE Office of Scientific and Technical Information (OSTI.GOV)

REYNOLDS,R.M.; SULLIVAN, T.M.; SMITH, S.

2007-01-01

The New York City midtown dispersion program, MID05, examined atmospheric transport in the deep urban canyons near Rockefeller Center. Little is known about air flow and hazardous gas dispersion under such conditions, since previous urban field experiments have focused on small to medium sized cities with much smaller street canyons and examined response over a much larger area. During August, 2005, a series of six gas tracer tests were conducted and sampling was conducted over a 2 km grid. A critical component of understanding gas movement in these studies is detailed wind and meteorological information in the study zone. Tomore » support data interpretation and modeling, several meteorological stations were installed at street level and on roof tops in Manhattan. In addition, meteorological data from airports and other weather instrumentation around New York City were collected. This document describes the meteorological component of the project and provides an outline of data file formats for the different instruments. These data provide enough detail to support highly-resolved computational simulations of gas transport in the study zone.« less

Investigating the influence of photocatalytic cool wall adoption on meteorology and air quality in the Los Angeles basin

NASA Astrophysics Data System (ADS)

Zhang, J.; Tang, X.; Levinson, R.; Destaillats, H.; Mohegh, A.; Li, Y.; Tao, W.; Liu, J.; Ban-Weiss, G. A.

2017-12-01

Solar reflective "cool materials" can be used to lower urban temperatures, useful for mitigating the urban heat island effect and adapting to the local impacts of climate change. While numerous past studies have investigated the climate impacts of cool surfaces, few studies have investigated their effects on air pollution. Meteorological changes from increases in surface albedo can lead to temperature and transport induced modifications in air pollutant concentrations. In an effort to maintain high albedos in polluted environments, cool surfaces can also be made using photocatalytic "self-cleaning" materials. These photocatalytic materials can also remove NOx from ambient air, with possible consequences on ambient gas and particle phase pollutant concentrations. In this research, we investigate the impact of widespread deployment of cool walls on urban meteorology and air pollutant concentrations in the Los Angeles basin. Both photocatalytic and standard (not photocatalytic) high albedo wall materials are investigated. Simulations using a coupled meteorology-chemistry model (WRF-Chem) show that cool walls could effectively decrease urban temperatures in the Los Angeles basin. Preliminary results indicate that meteorology-induced changes from adopting standard cool walls could lead to ozone concentration reductions of up to 0.5 ppb. NOx removal induced by photocatalytic materials was modeled by modifying the WRF-Chem dry deposition scheme, with deposition rates informed by laboratory measurements of various commercially available materials. Simulation results indicate that increased deposition of NOx by photocatalytic materials could increase ozone concentrations, analogous to the ozone "weekend effect" in which reduced weekend NOx emissions can lead to increases in ozone. The impacts of cool walls on particulate matter concentrations are also discussed. Changes in particulate matter concentrations are found to be driven by albedo-induced changes in air pollutant transport in the basin, temperature induced changes in photochemistry and aerosol phase partitioning, and changes to secondary organic aerosol.

Development of a comprehensive air quality modeling framework for a coastal urban airshed in south Texas

NASA Astrophysics Data System (ADS)

Farooqui, Mohmmed Zuber

Tropospheric ozone is one of the major air pollution problems affecting urban areas of United States as well as other countries in the world. Analysis of surface observed ozone levels in south and central Texas revealed several days exceeding 8-hour average ozone National Ambient of Air Quality Standards (NAAQS) over the past decade. Two major high ozone episodes were identified during September of 1999 and 2002. A photochemical modeling framework for the high ozone episodes in 1999 and 2002 were developed for the Corpus Christi urban airshed. The photochemical model was evaluated as per U.S. Environmental Protection Agency (EPA) recommended statistical methods and the models performed within the limits set by EPA. An emission impact assessment of various sources within the urban airshed was conducted using the modeling framework. It was noted that by nudging MM5 with surface observed meteorological parameters and sea-surface temperature, the coastal meteorological predictions improved. Consequently, refined meteorology helped the photochemical model to better predict peak ozone levels in urban airsheds along the coastal margins of Texas including in Corpus Christi. The emissions assessment analysis revealed that Austin and San Antonio areas were significantly affected by on-road mobile emissions from light-duty gasoline and heavy-duty diesel vehicles. The urban areas of San Antonio, Austin, and Victoria areas were estimated to be NOx sensitive. Victoria was heavily influenced by point sources in the region while Corpus Christi was influenced by both point and non-road mobile sources and was identified to be sensitive to VOC emissions. A rise in atmospheric temperature due to climate change potentially increase ozone exceedances and the peak ozone levels within the study region and this will be a major concern for air quality planners. This study noted that any future increase in ambient temperature would result in a significant increase in the urban and regional ozone levels within the modeling domain and it would also enhance the transported levels of ozone across the region. Overall, the photochemical modeling framework helped in evaluating the impact of various parameters affecting ozone air quality; and, it has the potential to be a tool for policy-makers to develop effective emissions control strategies under various regulatory and climate conditions.

Modelling the photochemical pollution over the metropolitan area of Porto Alegre, Brazil

NASA Astrophysics Data System (ADS)

Borrego, C.; Monteiro, A.; Ferreira, J.; Moraes, M. R.; Carvalho, A.; Ribeiro, I.; Miranda, A. I.; Moreira, D. M.

2010-01-01

The main purpose of this study is to evaluate the photochemical pollution over the Metropolitan Area of Porto Alegre (MAPA), Brazil, where high concentrations of ozone have been registered during the past years. Due to the restricted spatial coverage of the monitoring air quality network, a numerical modelling technique was selected and applied to this assessment exercise. Two different chemistry-transport models - CAMx and CALGRID - were applied for a summer period, driven by the MM5 meteorological model. The meteorological model performance was evaluated comparing its results to available monitoring data measured at the Porto Alegre airport. Validation results point out a good model performance. It was not possible to evaluate the chemistry models performance due to the lack of adequate monitoring data. Nevertheless, the model intercomparison between CAMx and CALGRID shows a similar behaviour in what concerns the simulation of nitrogen dioxide, but some discrepancies concerning ozone. Regarding the fulfilment of the Brazilian air quality targets, the simulated ozone concentrations surpass the legislated value in specific periods, mainly outside the urban area of Porto Alegre. The ozone formation is influenced by the emission of pollutants that act as precursors (like the nitrogen oxides emitted at Porto Alegre urban area and coming from a large refinery complex) and by the meteorological conditions.

Evaluating WRF Simulations of Urban Boundary Layer Processes during DISCOVER-AQ

NASA Astrophysics Data System (ADS)

Hegarty, J. D.; Henderson, J.; Lewis, J. R.; McGrath-Spangler, E. L.; Scarino, A. J.; Ferrare, R. A.; DeCola, P.; Welton, E. J.

2015-12-01

The accurate representation of processes in the planetary boundary layer (PBL) in meteorological models is of prime importance to air quality and greenhouse gas simulations as it governs the depth to which surface emissions are vertically mixed and influences the efficiency by which they are transported downwind. In this work we evaluate high resolution (~1 km) WRF simulations of PBL processes in the Washington DC - Baltimore and Houston urban areas during the respective DISCOVER-AQ 2011 and 2013 field campaigns using MPLNET micro-pulse lidar (MPL), mini-MPL, airborne high spectral resolution lidar (HSRL), Doppler wind profiler and CALIPSO satellite measurements along with complimentary surface and aircraft measurements. We will discuss how well WRF simulates the spatiotemporal variability of the PBL height in the urban areas and the development of fine-scale meteorological features such as bay and sea breezes that influence the air quality of the urban areas studied.

Urban Canopy Effects in Regional Climate Simulations - An Inter-Model Comparison

NASA Astrophysics Data System (ADS)

Halenka, T.; Huszar, P.; Belda, M.; Karlicky, J.

2017-12-01

To assess the impact of cities and urban surfaces on climate, the modeling approach is often used with inclusion of urban parameterization in land-surface interactions. This is especially important when going to higher resolution, which is common trend both in operational weather prediction and regional climate modelling. Model description of urban canopy related meteorological effects can, however, differ largely given especially the underlying surface models and the urban canopy parameterizations, representing a certain uncertainty. To assess this uncertainty is important for adaptation and mitigation measures often applied in the big cities, especially in connection to climate change perspective, which is one of the main task of the new project OP-PPR Proof of Concept UK. In this study we contribute to the estimation of this uncertainty by performing numerous experiments to assess the urban canopy meteorological forcing over central Europe on climate for the decade 2001-2010, using two regional climate models (RegCM4 and WRF) in 10 km resolution driven by ERA-Interim reanalyses, three surface schemes (BATS and CLM4.5 for RegCM4 and Noah for WRF) and five urban canopy parameterizations available: one bulk urban scheme, three single layer and a multilayer urban scheme. Effects of cities on urban and remote areas were evaluated. There are some differences in sensitivity of individual canopy model implementations to the UHI effects, depending on season and size of the city as well. Effect of reducing diurnal temperature range in cities (around 2 °C in summer mean) is noticeable in all simulations, independent to urban parameterization type and model, due to well-known warmer summer city nights. For the adaptation and mitigation purposes, rather than the average urban heat island intensity the distribution of it is more important providing the information on extreme UHI effects, e.g. during heat waves. We demonstrate that for big central European cities this effect can approach 10°C, even for not so big ones these extreme effects can go above 5°C.

The Atlanta Urban Heat Island Mitigation and Air Quality Modeling Project: How High-Resoution Remote Sensing Data Can Improve Air Quality Models

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William L.; Khan, Maudood N.

2006-01-01

The Atlanta Urban Heat Island and Air Quality Project had its genesis in Project ATLANTA (ATlanta Land use Analysis: Temperature and Air quality) that began in 1996. Project ATLANTA examined how high-spatial resolution thermal remote sensing data could be used to derive better measurements of the Urban Heat Island effect over Atlanta. We have explored how these thermal remote sensing, as well as other imaged datasets, can be used to better characterize the urban landscape for improved air quality modeling over the Atlanta area. For the air quality modeling project, the National Land Cover Dataset and the local scale Landpro99 dataset at 30m spatial resolutions have been used to derive land use/land cover characteristics for input into the MM5 mesoscale meteorological model that is one of the foundations for the Community Multiscale Air Quality (CMAQ) model to assess how these data can improve output from CMAQ. Additionally, land use changes to 2030 have been predicted using a Spatial Growth Model (SGM). SGM simulates growth around a region using population, employment and travel demand forecasts. Air quality modeling simulations were conducted using both current and future land cover. Meteorological modeling simulations indicate a 0.5 C increase in daily maximum air temperatures by 2030. Air quality modeling simulations show substantial differences in relative contributions of individual atmospheric pollutant constituents as a result of land cover change. Enhanced boundary layer mixing over the city tends to offset the increase in ozone concentration expected due to higher surface temperatures as a result of urbanization.

Megacities and Large Urban Complexes - WMO Role in Addressing Challenges and Opportunities

NASA Astrophysics Data System (ADS)

Terblanche, Deon; Jalkanen, Liisa

2013-04-01

Megacities and Large Urban Complexes - WMO Role in Addressing Challenges and Opportunities Deon E. Terblanche and Liisa Jalkanen dterblanche@wmo.int ljalkanen@wmo.int World Meteorological Organization, Geneva, Switzerland The 21st Century could amongst others, become known as the century in which our species has evolved from Homo sapiens to Homo urbanus. By now the urban population has surpassed the rural population and the rate of urbanization will continue at such a pace that by 2050 urban dwellers could outnumber their rural counterpart by more than two to one. Most of this growth in urban population will occur in developing countries and along coastal areas. Urbanization is to a large extent the outcome of humans seeking a better life through improved opportunities presented by high-density communities. Megacities and large urban complexes provide more job opportunities and social structures, better transport and communication links and a relative abundance of physical goods and services when compared to most rural areas. Unfortunately these urban complexes also present numerous social and environmental challenges. Urban areas differ from their surroundings by morphology, population density, and with high concentration of industrial activities, energy consumption and transport. They also pose unique challenges to atmospheric modelling and monitoring and create a multi-disciplinary spectrum of potential threats, including air pollution, which need to be addressed in an integrated way. These areas are also vulnerable to the changing climate and its implications to sea-level and extreme events, air quality and related health impacts. Many urban activities are significantly impacted by weather events that would not be considered to be of high impact in less densely populated areas. For instance, moderate precipitation events can cause flooding and landslides as modified urban catchments generally have higher run-off to rainfall ratios than their more pristine rural counterparts. The urban environment also provides numerous opportunities. One example being the better use of weather and environmental predictions to proactively optimize the functioning of the urban environment in terms of the use of energy, goods and services. Another is the providing of air quality forecasting services to benefit the health of the population. To address the challenges and opportunities facing megacities and large urban complexes, WMO has established the Global Atmosphere Watch (GAW) Urban Research Meteorology and Environment (GURME). Air pollution questions in urban areas, in particular megacities, is the main focus, building observational and modelling capabilities in developing countries through pilot projects and transfer of scientific expertise. GURME contributes to improving capabilities to handle meteorological and related features of air pollution by addressing end-to-end aspects of air quality, linking observational capabilities with the needs of chemical weather prediction, with the goal of providing high quality air quality services. Using examples from around the world but with specific reference to Africa, the unique challenges and opportunities related to megacities and large urban complexes, as perceived by the World Meteorological Organization (WMO) are highlighted.

Contribution of land use changes to meteorological parameters in Greater Jakarta: Case 17 January 2014

NASA Astrophysics Data System (ADS)

Nuryanto, D. E.; Pawitan, H.; Hidayat, R.; Aldrian, E.

2018-05-01

The impact of land use changes on meteorological parameters during a heavy rainfall event on 17 January 2014 in Greater Jakarta (GJ) was examined using the Weather Research and Forecasting (WRF) model. This study performed two experimental simulation methods. The first WRF simulation uses default land use (CTL). The second simulation applies the experiment by changing the size of urban and built-up land use (SCE). The Global Forecast System (GFS) data is applied to provide more realistic initial and boundary conditions for the nested model domains (3 km, 1 km). The simulations were initiated at 00:00 UTC January 13, 2014 and the period of modeling was equal to six days. The air temperature and the precipitation pattern in GJ shows a good agreement between the observed and simulated data. The results show a consistent significant contribution of urban development and accompany land use changes in air temperature and precipitation. According to the model simulation, urban and built-up land contributed about 6% of heavy rainfall and about 0.2 degrees of air temperatures in the morning. Simulations indicate that new urban developments led to an intensification and expansion of the rain area. The results can support the decision-making of flooding and watershed management.

Improving of local ozone forecasting by integrated models.

PubMed

Gradišar, Dejan; Grašič, Boštjan; Božnar, Marija Zlata; Mlakar, Primož; Kocijan, Juš

2016-09-01

This paper discuss the problem of forecasting the maximum ozone concentrations in urban microlocations, where reliable alerting of the local population when thresholds have been surpassed is necessary. To improve the forecast, the methodology of integrated models is proposed. The model is based on multilayer perceptron neural networks that use as inputs all available information from QualeAria air-quality model, WRF numerical weather prediction model and onsite measurements of meteorology and air pollution. While air-quality and meteorological models cover large geographical 3-dimensional space, their local resolution is often not satisfactory. On the other hand, empirical methods have the advantage of good local forecasts. In this paper, integrated models are used for improved 1-day-ahead forecasting of the maximum hourly value of ozone within each day for representative locations in Slovenia. The WRF meteorological model is used for forecasting meteorological variables and the QualeAria air-quality model for gas concentrations. Their predictions, together with measurements from ground stations, are used as inputs to a neural network. The model validation results show that integrated models noticeably improve ozone forecasts and provide better alert systems.

Urban air quality, meteorology and traffic linkages: Evidence from a sixteen-day particulate matter pollution event in December 2015, Beijing.

PubMed

Hu, Dongmei; Wu, Jianping; Tian, Kun; Liao, Lyuchao; Xu, Ming; Du, Yiman

2017-09-01

A heavy 16-day pollution episode occurred in Beijing from December 19, 2015 to January 3, 2016. The mean daily AQI and PM 2.5 were 240.44 and 203.6μg/m 3 . We analyzed the spatiotemporal characteristics of air pollutants, meteorology and road space speed during this period, then extended to reveal the combined effects of traffic restrictions and meteorology on urban air quality with observational data and a multivariate mutual information model. Results of spatiotemporal analysis showed that five pollution stages were identified with remarkable variation patterns based on evolution of PM 2.5 concentration and weather conditions. Southern sites (DX, YDM and DS) experienced heavier pollution than northern ones (DL, CP and WL). Stage P2 exhibited combined functions of meteorology and traffic restrictions which were delayed peak-clipping effects on PM 2.5 . Mutual information values of Air quality-Traffic-Meteorology (ATM-MI) revealed that additive functions of traffic restrictions, suitable relative humidity and temperature were more effective on the removal of fine particles and CO than NO 2 . Copyright © 2017. Published by Elsevier B.V.

Impact of regional afforestation on climatic conditions in metropolitan areas: case study of Copenhagen

NASA Astrophysics Data System (ADS)

Stysiak, Aleksander Andrzej; Bergen Jensen, Marina; Mahura, Alexander

2016-04-01

Like most other places, European metropolitan areas will face a range of climate-related challenges over the next decades that may influence the nature of urban life across the continent. Under future urbanization and climate change scenarios the well-being and comfort of the urban population might become progressively compromised. In urban areas, the effects of the warming climate will be accelerated by combination of Urban Heat Island effect (UHI) and extreme heat waves. The land cover composition directly influences atmospheric variability, and can either escalate or downscale the projected changes. Vegetation, forest ecosystems in particular, are anticipated to play an important role in modulating local and regional climatic conditions, and to be vital factor in the process of adapting cities to warming climate. This study investigates the impact of forest and land-cover change on formation and development of temperature regimes in the Copenhagen Metropolitan Area (CPH-MA). Potential to modify the UHI effect in CPH-MA is estimated. Using 2009 meteorological data, and up-to-date 2012 high resolution land-cover data we employed the online integrated meteorology-chemistry/aerosols Enviro-HIRLAM (Environment - High Resolution Limited Area Model) modeling system to simulate air temperature (at 2 meter height) fields for a selected period in July 2009. Employing research tools (such as METGRAF meteorological software and Geographical Information Systems) we then estimated the influence of different afforestation and urbanization scenarios with new forests being located after the Danish national afforestation plan, after proximity to the city center, after dominating wind characteristics, and urbanization taking place as densification of the existing conurbation. This study showed the difference in temperature up to 3.25°C, and the decrease in the spatial extent of temperature fields up to 68%, depending on the selected scenario. Performed simulations demonstrated that well-positioned and well-sized afforestation at the regional scale can significantly affect the spatial distribution, structure and intensity of the temperature field. This study points to vegetation having practical applications in urban and regional planning for modifying local climatic conditions. Keywords: Urban Heat Island, Afforestation, Land cover change, Urban planning, Climate change adaptation, Enviro-HIRLAM

Developing a methodology to predict PM10 concentrations in urban areas using generalized linear models.

PubMed

Garcia, J M; Teodoro, F; Cerdeira, R; Coelho, L M R; Kumar, Prashant; Carvalho, M G

2016-09-01

A methodology to predict PM10 concentrations in urban outdoor environments is developed based on the generalized linear models (GLMs). The methodology is based on the relationship developed between atmospheric concentrations of air pollutants (i.e. CO, NO2, NOx, VOCs, SO2) and meteorological variables (i.e. ambient temperature, relative humidity (RH) and wind speed) for a city (Barreiro) of Portugal. The model uses air pollution and meteorological data from the Portuguese monitoring air quality station networks. The developed GLM considers PM10 concentrations as a dependent variable, and both the gaseous pollutants and meteorological variables as explanatory independent variables. A logarithmic link function was considered with a Poisson probability distribution. Particular attention was given to cases with air temperatures both below and above 25°C. The best performance for modelled results against the measured data was achieved for the model with values of air temperature above 25°C compared with the model considering all ranges of air temperatures and with the model considering only temperature below 25°C. The model was also tested with similar data from another Portuguese city, Oporto, and results found to behave similarly. It is concluded that this model and the methodology could be adopted for other cities to predict PM10 concentrations when these data are not available by measurements from air quality monitoring stations or other acquisition means.

Air quality modelling in the Berlin-Brandenburg region using WRF-Chem v3.7.1: sensitivity to resolution of model grid and input data

NASA Astrophysics Data System (ADS)

Kuik, Friderike; Lauer, Axel; Churkina, Galina; Denier van der Gon, Hugo A. C.; Fenner, Daniel; Mar, Kathleen A.; Butler, Tim M.

2016-12-01

Air pollution is the number one environmental cause of premature deaths in Europe. Despite extensive regulations, air pollution remains a challenge, especially in urban areas. For studying summertime air quality in the Berlin-Brandenburg region of Germany, the Weather Research and Forecasting Model with Chemistry (WRF-Chem) is set up and evaluated against meteorological and air quality observations from monitoring stations as well as from a field campaign conducted in 2014. The objective is to assess which resolution and level of detail in the input data is needed for simulating urban background air pollutant concentrations and their spatial distribution in the Berlin-Brandenburg area. The model setup includes three nested domains with horizontal resolutions of 15, 3 and 1 km and anthropogenic emissions from the TNO-MACC III inventory. We use RADM2 chemistry and the MADE/SORGAM aerosol scheme. Three sensitivity simulations are conducted updating input parameters to the single-layer urban canopy model based on structural data for Berlin, specifying land use classes on a sub-grid scale (mosaic option) and downscaling the original emissions to a resolution of ca. 1 km × 1 km for Berlin based on proxy data including traffic density and population density. The results show that the model simulates meteorology well, though urban 2 m temperature and urban wind speeds are biased high and nighttime mixing layer height is biased low in the base run with the settings described above. We show that the simulation of urban meteorology can be improved when specifying the input parameters to the urban model, and to a lesser extent when using the mosaic option. On average, ozone is simulated reasonably well, but maximum daily 8 h mean concentrations are underestimated, which is consistent with the results from previous modelling studies using the RADM2 chemical mechanism. Particulate matter is underestimated, which is partly due to an underestimation of secondary organic aerosols. NOx (NO + NO2) concentrations are simulated reasonably well on average, but nighttime concentrations are overestimated due to the model's underestimation of the mixing layer height, and urban daytime concentrations are underestimated. The daytime underestimation is improved when using downscaled, and thus locally higher emissions, suggesting that part of this bias is due to deficiencies in the emission input data and their resolution. The results further demonstrate that a horizontal resolution of 3 km improves the results and spatial representativeness of the model compared to a horizontal resolution of 15 km. With the input data (land use classes, emissions) at the level of detail of the base run of this study, we find that a horizontal resolution of 1 km does not improve the results compared to a resolution of 3 km. However, our results suggest that a 1 km horizontal model resolution could enable a detailed simulation of local pollution patterns in the Berlin-Brandenburg region if the urban land use classes, together with the respective input parameters to the urban canopy model, are specified with a higher level of detail and if urban emissions of higher spatial resolution are used.

Simulating urban-scale air pollutants and their predicting capabilities over the Seoul metropolitan area.

PubMed

Park, Il-Soo; Lee, Suk-Jo; Kim, Cheol-Hee; Yoo, Chul; Lee, Yong-Hee

2004-06-01

Urban-scale air pollutants for sulfur dioxide, nitrogen dioxide, particulate matter with aerodynamic diameter > or = 10 microm, and ozone (O3) were simulated over the Seoul metropolitan area, Korea, during the period of July 2-11, 2002, and their predicting capabilities were discussed. The Air Pollution Model (TAPM) and the highly disaggregated anthropogenic and the biogenic gridded emissions (1 km x 1 km) recently prepared by the Korean Ministry of Environment were applied. Wind fields with observational nudging in the prognostic meteorological model TAPM are optionally adopted to comparatively examine the meteorological impact on the prediction capabilities of urban-scale air pollutants. The result shows that the simulated concentrations of secondary air pollutant largely agree with observed levels with an index of agreement (IOA) of >0.6, whereas IOAs of approximately 0.4 are found for most primary pollutants in the major cities, reflecting the quality of emission data in the urban area. The observationally nudged wind fields with higher IOAs have little effect on the prediction for both primary and secondary air pollutants, implying that the detailed wind field does not consistently improve the urban air pollution model performance if emissions are not well specified. However, the robust highest concentrations are better described toward observations by imposing observational nudging, suggesting the importance of wind fields for the predictions of extreme concentrations such as robust highest concentrations, maximum levels, and >90th percentiles of concentrations for both primary and secondary urban-scale air pollutants.

Introduction of the Mobile Platform for the Meteorological Observations in Seoul Metropolitan City of Korea

NASA Astrophysics Data System (ADS)

Baek, K. T.; Lee, S.; Kang, M.; Lee, G.

2016-12-01

Traffic accidents due to adverse weather such as fog, heavy rainfall, flooding and road surface freezing have been increasing in Korea. To reduce damages caused by the severe weather on the road, a forecast service of combined real-time road-wise weather and the traffic situation is required. Conventional stationary meteorological observations in sparse location system are limited to observe the detailed road environment. For this reason, a mobile meteorological observation platform has been coupled in Weather Information Service Engine (WISE) which is the prototype of urban-scale high resolution weather prediction system in Seoul metropolitan area of Korea in early August 2016. The instruments onboard are designed to measure 15 meteorological parameters; pressure, temperature, relative humidity, precipitation, up/down net radiation, up/down longwave radiation, up/down shortwave radiation, road surface condition, friction coefficient, water depth, wind direction and speed. The observations from mobile platform show a distinctive advantage of data collection in need for road conditions and inputs for the numerical forecast model. In this study, we introduce and examine the feasibility of mobile observations in urban weather prediction and applications.

ONE-ATMOSPHERE DYNAMICS DESCRIPTION IN THE MODELS-3 COMMUNITY MULTI-SCALE QUALITY (CMAQ) MODELING SYSTEM

EPA Science Inventory

This paper proposes a general procedure to link meteorological data with air quality models, such as U.S. EPA's Models-3 Community Multi-scale Air Quality (CMAQ) modeling system. CMAQ is intended to be used for studying multi-scale (urban and regional) and multi-pollutant (ozon...

A joint modelling exercise designed to assess the respective impact of emission changes and meteorological variability on the observed air quality trends in major urban hotspots.

NASA Astrophysics Data System (ADS)

Colette, Augustin; Bessagnet, Bertrand; Dangiola, Ariela; D'Isidoro, Massimo; Gauss, Michael; Granier, Claire; Hodnebrog, Øivind; Jakobs, Hermann; Kanakidou, Maria; Khokhar, Fahim; Law, Kathy; Maurizi, Alberto; Meleux, Frederik; Memmesheimer, Michael; Nyiri, Agnes; Rouil, Laurence; Stordal, Frode; Tampieri, Francesco

2010-05-01

With the growth of urban agglomerations, assessing the drivers of variability of air quality in and around the main anthropogenic emission hotspots has become a major societal concern as well as a scientific challenge. These drivers include emission changes and meteorological variability; both of them can be investigated by means of numerical modelling of trends over the past few years. A collaborative effort has been developed in the framework of the CityZen European project to address this question. Several chemistry and transport models (CTMs) are deployed in this activity: four regional models (BOLCHEM, CHIMERE, EMEP and EURAD) and three global models (CTM2, MOZART, and TM4). The period from 1998 to 2007 has been selected for the historic reconstruction. The focus for the present preliminary presentation is Europe. A consistent set of emissions is used by all partners (EMEP for the European domain and IPCC-AR5 beyond) while a variety of meteorological forcing is used to gain robustness in the ensemble spread amongst models. The results of this experiment will be investigated to address the following questions: - Is the envelope of models able to reproduce the observed trends of the key chemical constituents? - How the variability amongst models changes in time and space and what does it tell us about the processes driving the observed trends? - Did chemical regimes and aerosol formation processes changed in selected hotspots? Answering the above questions will contribute to fulfil the ultimate goal of the present study: distinguishing the respective contribution of meteorological variability and emissions changes on air quality trends in major anthropogenic emissions hotspots.

PREDICTING THE RELATIVE IMPACTS OF URBAN DEVELOPMENT POLICIES AND ON-ROAD VEHICLE TECHNOLOGIES ON AIR QUALITY IN THE UNITED STATES: MODELING AND ANALYSIS OF A CASE STUDY IN AUSTIN, TEXAS

EPA Science Inventory

Urban development results in changes to land use and land cover and, consequently, to biogenic and anthropogenic emissions, meteorological processes, and processes such as dry deposition that influence future predictions of air quality. This study examines the impacts of alter...

An Investigation of the Influence of Urban Areas on Rainfall Using a Cloud-Mesoscale Model and the TRMM Satellite

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Starr, David O'C (Technical Monitor)

2001-01-01

A recent paper by Shepherd and Pierce (conditionally accepted to Journal of Applied Meteorology) used rainfall data from the Precipitation Radar on NASA's Tropical Rainfall Measuring Mission's (TRMM) satellite to identify warm season rainfall anomalies downwind of major urban areas. A convective-mesoscale model with extensive land-surface processes is employed to (a) determine if an urban heat island (UHI) thermal perturbation can induce a dynamic response to affect rainfall processes and (b) quantify the impact of the following three factors on the evolution of rainfall: (1) urban surface roughness, (2) magnitude of the UHI temperature anomaly, and (3) physical size of the UHI temperature anomaly. The sensitivity experiments are achieved by inserting a slab of land with urban properties (e.g. roughness length, albedo, thermal character) within a rural surface environment and varying the appropriate lower boundary condition parameters. Early analysis suggests that urban surface roughness (through turbulence and low-level convergence) may control timing and initial location of UHI-induced convection. The magnitude of the heat island appears to be closely linked to the total rainfall amount with minor impact on timing and location. The physical size of the city may predominantly impact on the location of UHI-induced rainfall anomaly. The UHI factor parameter space will be thoroughly investigated with respect to their effects on rainfall amount, location, and timing. This study extends prior numerical investigations of the impact of urban surfaces on meteorological processes, particularly rainfall development. The work also contains several novel aspects, including the application of a high-resolution (less than I km) cloud-mesoscale model to investigate urban-induce rainfall process; investigation of thermal magnitude of the UHI on rainfall process; and investigation of UHI physical size on rainfall processes.

Remote Sensing Characterization of the Urban Landscape for Improvement of Air Quality Modeling

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Khan, Maudood

2005-01-01

The urban landscape is inherently complex and this complexity is not adequately captured in air quality models, particularly the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban growth projections as improved inputs to the meteorology component of the CMAQ model focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, in moderating ground-level ozone and air temperature, compared to "business as usual" simulations in which heat island mitigation strategies are not applied. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data has been found to better characterize low densityhburban development as compared with USGS 1 km land use/land cover data that have traditionally been used in modeling. Air quality prediction for fiture scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the state Environmental Protection agency to evaluate how these transportation plans will affect fbture air quality.

Simulating gas and particulate pollution over the Middle East and the state of Qatar using a 3-D regional air quality modeling system

NASA Astrophysics Data System (ADS)

Fountoukis, Christos; Gladich, Ivan; Ayoub, Mohammed; Kais, Sabre; Ackermann, Luis; Skillern, Adam

2016-04-01

The rapid urbanization, industrialization and economic expansion in the Middle East have led to increased levels of atmospheric pollution with important implications for human health and climate. We applied the online-coupled meteorological and chemical transport Weather Research and Forecasting/Chemistry (WRF-Chem) model over the Middle Eastern domain, to simulate the concentration of gas and aerosols with a special focus over the state of Qatar. WRF-Chem was set to simulate pollutant concentrations along with the meteorology-chemistry interactions through the related direct, indirect and semi-direct feedback mechanisms. A triple-nested domain configuration was used with a high grid resolution (1x1 km2) over the region of Qatar. Model predictions are evaluated against intensive measurements of meteorological parameters (temperature, relative humidity and wind speed) as well as ozone and particulate matter taken from various measurement stations throughout Doha, Qatar during summer 2015. The ability of the model to capture the temporal and spatial variability of the observations is assessed and possible reasons for the model bias are explored through sensitivity tests. Emissions of both fine and coarse mode particles from construction activities in large urban Middle Eastern environments comprise a major pollution source that is unaccounted for in emission inventories used so far in large scale models for this part of the world.

Development and application of artificial neural network models to estimate values of a complex human thermal comfort index associated with urban heat and cool island patterns using air temperature data from a standard meteorological station

NASA Astrophysics Data System (ADS)

Moustris, Konstantinos; Tsiros, Ioannis X.; Tseliou, Areti; Nastos, Panagiotis

2018-04-01

The present study deals with the development and application of artificial neural network models (ANNs) to estimate the values of a complex human thermal comfort-discomfort index associated with urban heat and cool island conditions inside various urban clusters using as only inputs air temperature data from a standard meteorological station. The index used in the study is the Physiologically Equivalent Temperature (PET) index which requires as inputs, among others, air temperature, relative humidity, wind speed, and radiation (short- and long-wave components). For the estimation of PET hourly values, ANN models were developed, appropriately trained, and tested. Model results are compared to values calculated by the PET index based on field monitoring data for various urban clusters (street, square, park, courtyard, and gallery) in the city of Athens (Greece) during an extreme hot weather summer period. For the evaluation of the predictive ability of the developed ANN models, several statistical evaluation indices were applied: the mean bias error, the root mean square error, the index of agreement, the coefficient of determination, the true predictive rate, the false alarm rate, and the Success Index. According to the results, it seems that ANNs present a remarkable ability to estimate hourly PET values within various urban clusters using only hourly values of air temperature. This is very important in cases where the human thermal comfort-discomfort conditions have to be analyzed and the only available parameter is air temperature.

Development and application of artificial neural network models to estimate values of a complex human thermal comfort index associated with urban heat and cool island patterns using air temperature data from a standard meteorological station.

PubMed

Moustris, Konstantinos; Tsiros, Ioannis X; Tseliou, Areti; Nastos, Panagiotis

2018-04-11

The present study deals with the development and application of artificial neural network models (ANNs) to estimate the values of a complex human thermal comfort-discomfort index associated with urban heat and cool island conditions inside various urban clusters using as only inputs air temperature data from a standard meteorological station. The index used in the study is the Physiologically Equivalent Temperature (PET) index which requires as inputs, among others, air temperature, relative humidity, wind speed, and radiation (short- and long-wave components). For the estimation of PET hourly values, ANN models were developed, appropriately trained, and tested. Model results are compared to values calculated by the PET index based on field monitoring data for various urban clusters (street, square, park, courtyard, and gallery) in the city of Athens (Greece) during an extreme hot weather summer period. For the evaluation of the predictive ability of the developed ANN models, several statistical evaluation indices were applied: the mean bias error, the root mean square error, the index of agreement, the coefficient of determination, the true predictive rate, the false alarm rate, and the Success Index. According to the results, it seems that ANNs present a remarkable ability to estimate hourly PET values within various urban clusters using only hourly values of air temperature. This is very important in cases where the human thermal comfort-discomfort conditions have to be analyzed and the only available parameter is air temperature.

A review of methods for predicting air pollution dispersion

NASA Technical Reports Server (NTRS)

Mathis, J. J., Jr.; Grose, W. L.

1973-01-01

Air pollution modeling, and problem areas in air pollution dispersion modeling were surveyed. Emission source inventory, meteorological data, and turbulent diffusion are discussed in terms of developing a dispersion model. Existing mathematical models of urban air pollution, and highway and airport models are discussed along with their limitations. Recommendations for improving modeling capabilities are included.

Development and testing of meteorology and air dispersion models for Mexico City

NASA Astrophysics Data System (ADS)

Williams, M. D.; Brown, M. J.; Cruz, X.; Sosa, G.; Streit, G.

Los Alamos National Laboratory and Instituto Mexicano del Petróleo are completing a joint study of options for improving air quality in Mexico City. We have modified a three-dimensional, prognostic, higher-order turbulence model for atmospheric circulation (HOTMAC) and a Monte Carlo dispersion and transport model (RAPTAD) to treat domains that include an urbanized area. We used the meteorological model to drive models which describe the photochemistry and air transport and dispersion. The photochemistry modeling is described in a separate paper. We tested the model against routine measurements and those of a major field program. During the field program, measurements included: (1) lidar measurements of aerosol transport and dispersion, (2) aircraft measurements of winds, turbulence, and chemical species aloft, (3) aircraft measurements of skin temperatures, and (4) Tethersonde measurements of winds and ozone. We modified the meteorological model to include provisions for time-varying synoptic-scale winds, adjustments for local wind effects, and detailed surface-coverage descriptions. We developed a new method to define mixing-layer heights based on model outputs. The meteorology and dispersion models were able to provide reasonable representations of the measurements and to define the sources of some of the major uncertainties in the model-measurement comparisons.

Acceptance criteria for urban dispersion model evaluation

NASA Astrophysics Data System (ADS)

Hanna, Steven; Chang, Joseph

2012-05-01

The authors suggested acceptance criteria for rural dispersion models' performance measures in this journal in 2004. The current paper suggests modified values of acceptance criteria for urban applications and tests them with tracer data from four urban field experiments. For the arc-maximum concentrations, the fractional bias should have a magnitude <0.67 (i.e., the relative mean bias is less than a factor of 2); the normalized mean-square error should be <6 (i.e., the random scatter is less than about 2.4 times the mean); and the fraction of predictions that are within a factor of two of the observations (FAC2) should be >0.3. For all data paired in space, for which a threshold concentration must always be defined, the normalized absolute difference should be <0.50, when the threshold is three times the instrument's limit of quantification (LOQ). An overall criterion is then applied that the total set of acceptance criteria should be satisfied in at least half of the field experiments. These acceptance criteria are applied to evaluations of the US Department of Defense's Joint Effects Model (JEM) with tracer data from US urban field experiments in Salt Lake City (U2000), Oklahoma City (JU2003), and Manhattan (MSG05 and MID05). JEM includes the SCIPUFF dispersion model with the urban canopy option and the urban dispersion model (UDM) option. In each set of evaluations, three or four likely options are tested for meteorological inputs (e.g., a local building top wind speed, the closest National Weather Service airport observations, or outputs from numerical weather prediction models). It is found that, due to large natural variability in the urban data, there is not a large difference between the performance measures for the two model options and the three or four meteorological input options. The more detailed UDM and the state-of-the-art numerical weather models do provide a slight improvement over the other options. The proposed urban dispersion model acceptance criteria are satisfied at over half of the field experiments.

NY-uHMT: A dense hydro-meteorological network to characterize urban land-atmosphere interactions

NASA Astrophysics Data System (ADS)

Ramamurthy, P.; Lakhankar, T.; Khanbilvardi, R.; Devineni, N.

2016-12-01

Most people in the US live in large Metropolitan areas that have a dense urban core in the center, dominated by built surfaces and surrounded by residential/suburban areas that consist a mix of built, vegetated and permeable surfaces. This creates a gradient in the hydro-meteorological environment giving rise to complex land-atmosphere interactions. Current modeling platforms and observational techniques like tower measurements do not adequately account for the underlying heterogeneity. To address this critical gap in our understanding we have instituted a dense network of sensors in the New York Metropolitan area. This unique urban sensor network consists of instrumentation to monitor soil moisture at multiple depths along with air temperature, relative humidity and precipitation, with room to add additional sensors in the future. The network is autonomous and connected to a centralized server using cellular towers. Apart from describing the spatial variability in hydro-meteorological quantities the network will also aid in conducting high-resolution numerical simulations to study and forecast urban weather and climate. In one such simulation conducted to partition the influence of storage flux, wind pattern and circulation and soil moisture deficit on urban heat island intensity (UHI), we found that the daily variability in UHI in NYC was sensitive to available energy and wind pattern. The long-term trend in UHI was however related to soil moisture deficit. In fact a prolonged heat wave period witnessed during summer 2006 correlated well with an extended dry period and the daily UHI in NYC almost doubled. Moreover, the urban soils also suffered from high degree of dessication, owing to drier urban boundary layer.

Temporal dynamic of malaria in a suburban area along the Niger River.

PubMed

Sissoko, Mahamadou Soumana; Sissoko, Kourane; Kamate, Bourama; Samake, Yacouba; Goita, Siaka; Dabo, Abdoulaye; Yena, Mama; Dessay, Nadine; Piarroux, Renaud; Doumbo, Ogobara K; Gaudart, Jean

2017-10-23

Even if rainfall and temperature are factors classically associated to malaria, little is known about other meteorological factors, their variability and combinations related to malaria, in association with river height variations. Furthermore, in suburban area, urbanization and growing population density should be assessed in relation to these environmental factors. The aim of this study was to assess the impact of combined environmental, meteorological and hydrological factors on malaria incidence through time in the context of urbanization. Population observational data were prospectively collected. Clinical malaria was defined as the presence of parasites in addition to clinical symptoms. Meteorological and hydrological factors were measured daily. For each factors variation indices were estimated. Urbanization was yearly estimated assessing satellite imaging and field investigations. Principal component analysis was used for dimension reduction and factors combination. Lags between malaria incidences and the main components were assessed by cross-correlation functions. Generalized additive model was used to assess relative impact of different environmental components, taking into account lags, and modelling non-linear relationships. Change-point analysis was used to determine transmission periods within years. Malaria incidences were dominated by annual periodicity and varied through time without modification of the dynamic, with no impact of the urbanization. The main meteorological factor associated with malaria was a combination of evaporation, humidity and rainfall, with a lag of 3 months. The relationship between combined temperature factors showed a linear impact until reaching high temperatures limiting malaria incidence, with a lag 3.25 months. Height and variation of the river were related to malaria incidence (respectively 6 week lag and no lag). The study emphasizes no decreasing trend of malaria incidence despite accurate access to care and control strategies in accordance to international recommendations. Furthermore, no decreasing trend was showed despite the urbanization of the area. Malaria transmission remain increase 3 months after the beginning of the dry season. Addition to evaporation versus humidity/rainfall, nonlinear relationship for temperature and river height and variations have to be taken into account when implementing malaria control programmes.

The water balance of the urban Salt Lake Valley: a multiple-box model validated by observations

NASA Astrophysics Data System (ADS)

Stwertka, C.; Strong, C.

2012-12-01

A main focus of the recently awarded National Science Foundation (NSF) EPSCoR Track-1 research project "innovative Urban Transitions and Arid-region Hydro-sustainability (iUTAH)" is to quantify the primary components of the water balance for the Wasatch region, and to evaluate their sensitivity to climate change and projected urban development. Building on the multiple-box model that we developed and validated for carbon dioxide (Strong et al 2011), mass balance equations for water in the atmosphere and surface are incorporated into the modeling framework. The model is used to determine how surface fluxes, ground-water transport, biological fluxes, and meteorological processes regulate water cycling within and around the urban Salt Lake Valley. The model is used to evaluate the hypotheses that increased water demand associated with urban growth in Salt Lake Valley will (1) elevate sensitivity to projected climate variability and (2) motivate more attentive management of urban water use and evaporative fluxes.

Influences of land cover types, meteorological conditions, anthropogenic heat and urban area on surface urban heat island in the Yangtze River Delta Urban Agglomeration.

PubMed

Du, Hongyu; Wang, Duoduo; Wang, Yuanyuan; Zhao, Xiaolei; Qin, Fei; Jiang, Hong; Cai, Yongli

2016-11-15

Urban heat islands (UHIs) reflect the localized impact of human activities on thermal fields. In this study, we assessed the surface UHI and its relationship with types of land, meteorological conditions, anthropogenic heat sources and urban areas in the Yangtze River Delta Urban Agglomeration (YRDUA) with the aid of remote sensing data, statistical data and meteorological data. The results showed that the UHI intensity in YRDUA was the strongest (0.84°C) in summer, followed by 0.81°C in autumn, 0.78°C in spring and 0.53°C in winter. The daytime UHI intensity is 0.98°C, which is higher than the nighttime UHI intensity of 0.50°C. Then, the relationship between the UHI intensity and several factors such as meteorological conditions, anthropogenic heat sources and the urban area were analysed. The results indicated that there was an insignificant correlation between population density and the UHI intensity. Energy consumption, average temperature and urban area had a significant positive correlation with UHI intensity. However, the average wind speed and average precipitation were significantly negatively correlated with UHI intensity. This study provides insight into the regional climate characteristics and a scientific basis for city layout. Copyright © 2016 Elsevier B.V. All rights reserved.

The passive control of air pollution exposure in Dublin, Ireland: a combined measurement and modelling case study.

PubMed

Gallagher, J; Gill, L W; McNabola, A

2013-08-01

This study investigates the potential real world application of passive control systems to reduce personal pollutant exposure in an urban street canyon in Dublin, Ireland. The implementation of parked cars and/or low boundary walls as a passive control system has been shown to minimise personal exposure to pollutants on footpaths in previous investigations. However, previous research has been limited to generic numerical modelling studies. This study combines real-time traffic data, meteorological conditions and pollution concentrations, in a real world urban street canyon before and after the implementation of a passive control system. Using a combination of field measurements and numerical modelling this study assessed the potential impact of passive controls on personal exposure to nitric oxide (NO) concentrations in the street canyon in winter conditions. A calibrated numerical model of the urban street canyon was developed, taking into account the variability in traffic and meteorological conditions. The modelling system combined the computational fluid dynamic (CFD) simulations and a semi-empirical equation, and demonstrated a good agreement with measured field data collected in the street canyon. The results indicated that lane distribution, fleet composition and vehicular turbulence all affected pollutant dispersion, in addition to the canyon geometry and local meteorological conditions. The introduction of passive controls displayed mixed results for improvements in air quality on the footpaths for different wind and traffic conditions. Parked cars demonstrated the most comprehensive passive control system with average improvements in air quality of up to 15% on the footpaths. This study highlights the potential of passive controls in a real street canyon to increase dispersion and improve air quality at street level. Copyright © 2013 Elsevier B.V. All rights reserved.

The Influence of Urban Planning Affected Static and Stable Meteorological Field on Air Pollution

NASA Astrophysics Data System (ADS)

Zhang, Yue; Zhang, Liyuan; Zhang, Yunwei

2018-02-01

Accompany with the rapid urbanized and industrialized process, the built-up area and the number of high-rise buildings increased fast. Urban air quality is facing with the challenge caused by the rapid increase in energy consumption, motor vehicles owned, and the city construction. Long term high precision analysis on Beijing-Tianjin-Hebei region has been conducted in this article, so as to explore the influence of rapid increase in urban size and tall building amount on occurrence frequency of urban static and stable meteorological conditions as well as the contribution to urban PM2.5 pollution.

Analysis of observed surface ozone in the dry season over Eastern Thailand during 1997-2012

NASA Astrophysics Data System (ADS)

Assareh, Nosha; Prabamroong, Thayukorn; Manomaiphiboon, Kasemsan; Theramongkol, Phunsak; Leungsakul, Sirakarn; Mitrjit, Nawarat; Rachiwong, Jintarat

2016-09-01

This study analyzed observed surface ozone (O3) in the dry season over a long-term period of 1997-2012 for the eastern region of Thailand and incorporated several technical tools or methods in investigating different aspects of O3. The focus was the urbanized and industrialized coastal areas recently recognized as most O3-polluted areas. It was found that O3 is intensified most in the dry-season months when meteorological conditions are favorable to O3 development. The diurnal variations of O3 and its precursors show the general patterns of urban background. From observational O3 isopleth diagrams and morning ratios of non-methane volatile organic compounds (NMVOC) and nitrogen oxides (NOx), the chemical regime of O3 formation was identified as VOC-sensitive, and the degree of VOC sensitivity tends to increase over the years, suggesting emission control on VOC to be suitable for O3 management. Both total oxidant analysis and back-trajectory modeling (together with K-means clustering) indicate the potential role of regional transport or influence in enhancing surface O3 level over the study areas. A meteorological adjustment with generalized linear modeling was performed to statistically exclude meteorological effects on the variability of O3. Local air-mass recirculation factor was included in the modeling to support the coastal application. The derived trends in O3 based on the meteorological adjustment were found to be significantly positive using a Mann-Kendall test with block bootstrapping.

The impact of urbanization during half a century on surface meteorology based on WRF model simulations over National Capital Region, India

NASA Astrophysics Data System (ADS)

Sati, Ankur Prabhat; Mohan, Manju

2017-10-01

An estimated 50% of the global population lives in the urban areas, and this percentage is projected to reach around 69% by the year 2050 (World Urbanization Prospects 2009). There is a considerable growth of urban and built-up area during the recent decades over National Capital Region (NCR) of India (17-fold increase in the urban extent). The proposed study estimates the land use land cover changes particularly changes to urban class from other land use types such as croplands, shrubland, open areas, and water bodies and quantify these changes for a span of about five decades. Further, the impact of these land use/land cover changes is examined on spatial and temporal variations of meteorological parameters using the Weather Research and Forecast (WRF) Model. The urbanized areas appear to be one of the regions with highest changes in the values of the fluxes and temperatures where during daytime, the surface sensible heat flux values show a noticeable increase of 60-70 W m-2 which commensurate with increase in urbanization. Similarly, the nighttime LST and T2m show an increase of 3-5 and 2-3 K, respectively. The diurnal temperature range (DTR) of LST and surface temperature also shows a decrease of about 5 and 2-3 K, respectively, with increasing urbanization. Significant decrease in the magnitude of surface winds and relative humidity is also observed over the areas converted to urban form over a period of half a century. The impacts shown here have serious implications on human health, energy consumption, ventilation, and atmospheric pollution.

Application of an integrated Weather Research and Forecasting (WRF)/CALPUFF modeling tool for source apportionment of atmospheric pollutants for air quality management: A case study in the urban area of Benxi, China.

PubMed

Wu, Hao; Zhang, Yan; Yu, Qi; Ma, Weichun

2018-04-01

In this study, the authors endeavored to develop an effective framework for improving local urban air quality on meso-micro scales in cities in China that are experiencing rapid urbanization. Within this framework, the integrated Weather Research and Forecasting (WRF)/CALPUFF modeling system was applied to simulate the concentration distributions of typical pollutants (particulate matter with an aerodynamic diameter <10 μm [PM 10 ], sulfur dioxide [SO 2 ], and nitrogen oxides [NO x ]) in the urban area of Benxi. Statistical analyses were performed to verify the credibility of this simulation, including the meteorological fields and concentration fields. The sources were then categorized using two different classification methods (the district-based and type-based methods), and the contributions to the pollutant concentrations from each source category were computed to provide a basis for appropriate control measures. The statistical indexes showed that CALMET had sufficient ability to predict the meteorological conditions, such as the wind fields and temperatures, which provided meteorological data for the subsequent CALPUFF run. The simulated concentrations from CALPUFF showed considerable agreement with the observed values but were generally underestimated. The spatial-temporal concentration pattern revealed that the maximum concentrations tended to appear in the urban centers and during the winter. In terms of their contributions to pollutant concentrations, the districts of Xihu, Pingshan, and Mingshan all affected the urban air quality to different degrees. According to the type-based classification, which categorized the pollution sources as belonging to the Bengang Group, large point sources, small point sources, and area sources, the source apportionment showed that the Bengang Group, the large point sources, and the area sources had considerable impacts on urban air quality. Finally, combined with the industrial characteristics, detailed control measures were proposed with which local policy makers could improve the urban air quality in Benxi. In summary, the results of this study showed that this framework has credibility for effectively improving urban air quality, based on the source apportionment of atmospheric pollutants. The authors endeavored to build up an effective framework based on the integrated WRF/CALPUFF to improve the air quality in many cities on meso-micro scales in China. Via this framework, the integrated modeling tool is accurately used to study the characteristics of meteorological fields, concentration fields, and source apportionments of pollutants in target area. The impacts of classified sources on air quality together with the industrial characteristics can provide more effective control measures for improving air quality. Through the case study, the technical framework developed in this study, particularly the source apportionment, could provide important data and technical support for policy makers to assess air pollution on the scale of a city in China or even the world.

Investigation of Future Thermal Comforts in a Tropical Megacity Using Coupling of Energy Balance Model and Large Eddy Simulation

NASA Astrophysics Data System (ADS)

Sueishi, T.; Yucel, M.; Ashie, Y.; Varquez, A. C. G.; Inagaki, A.; Darmanto, N. S.; Nakayoshi, M.; Kanda, M.

2017-12-01

Recently, temperature in urban areas continue to rise as an effect of climate change and urbanization. Specifically, Asian megacities are projected to expand rapidly resulting to serious in the future atmospheric environment. Thus, detailed analysis of urban meteorology for Asian megacities is needed to prescribe optimum against these negative climate modifications. A building-resolving large eddy simulation (LES) coupled with an energy balance model is conducted for a highly urbanized district in central Jakarta on typical daytime hours. Five cases were considered; case 1 utilizes present urban scenario and four cases representing different urban configurations in 2050. The future configurations were based on representative concentration pathways (RCP) and shared socio-economic pathways (SSP). Building height maps and land use maps of simulation domains are shown in the attached figure (top). Case 1 3 focuses on the difference of future scenarios. Case 1 represents current climatic and urban conditions, case 2 and 3 was an idealized future represented by RCP2.6/SSP1 and RCP8.5/SSP3, respectively. More complex urban morphology was applied in case 4, vegetation and building area were changed in case 5. Meteorological inputs and anthropogenic heat emission (AHE) were calculated using Weather Research and Forecasting (WRF) model (Varquez et al [2017]). Sensible and latent heat flux from surfaces were calculated using an energy balance model (Ashie et al [2011]), with considers multi-reflection, evapotranspiration and evaporation. The results of energy balance model (shown in the middle line of figure), in addition to WRF outputs, were used as input into the PArallelized LES Model (PALM) (Raasch et al [2001]). From standard new effective temperature (SET*) which included the effects of temperature, wind speed, humidity and radiation, thermal comfort in urban area was evaluated. SET* contours at 1 m height are shown in the bottom line of the figure. Extreme climate change increase average SET* as expected; however, construction of dense high-rise buildings (case 2) can minimize this effect due to increased shading throughout the district. Acknowledgement: This research was supported by the Environment Research and Technology Development Fund (S-14) of the Ministry of the Environment, Japan.

A dynamic aerodynamic resistance approach to calculate high resolution sensible heat fluxes in urban areas

NASA Astrophysics Data System (ADS)

Crawford, Ben; Grimmond, Sue; Kent, Christoph; Gabey, Andrew; Ward, Helen; Sun, Ting; Morrison, William

2017-04-01

Remotely sensed data from satellites have potential to enable high-resolution, automated calculation of urban surface energy balance terms and inform decisions about urban adaptations to environmental change. However, aerodynamic resistance methods to estimate sensible heat flux (QH) in cities using satellite-derived observations of surface temperature are difficult in part due to spatial and temporal variability of the thermal aerodynamic resistance term (rah). In this work, we extend an empirical function to estimate rah using observational data from several cities with a broad range of surface vegetation land cover properties. We then use this function to calculate spatially and temporally variable rah in London based on high-resolution (100 m) land cover datasets and in situ meteorological observations. In order to calculate high-resolution QH based on satellite-observed land surface temperatures, we also develop and employ novel methods to i) apply source area-weighted averaging of surface and meteorological variables across the study spatial domain, ii) calculate spatially variable, high-resolution meteorological variables (wind speed, friction velocity, and Obukhov length), iii) incorporate spatially interpolated urban air temperatures from a distributed sensor network, and iv) apply a modified Monte Carlo approach to assess uncertainties with our results, methods, and input variables. Modeled QH using the aerodynamic resistance method is then compared to in situ observations in central London from a unique network of scintillometers and eddy-covariance measurements.

Long-term visibility data in the UK - how does visibility vary with meteorological and pollutant parameters?

NASA Astrophysics Data System (ADS)

Singh, Ajit; Bloss, William J.; Pope, Francis D.

2016-04-01

Poor visibility can be an indicator of poor air quality. Moreover, degradation in visibility can be hazardous to human safety; for example, low visibility can lead to accidents particularly during winter when fogs are prevalent. The present quantitative analysis attempts to explain the influence of aerosol concentration and composition, and meteorology on long-term UK visibility. We use visibility data from eight UK meteorological stations which have been running since the 1950s. The site locations include urban, rural and marine environments. Overall, most stations show a long term trend of visibility increase, which is indicative of reductions in aerosol pollution, especially in urban areas. Additionally, results at all sites show a very clear dependence on relative humidity, indicating the importance of aerosol hygroscopicity on the ability of aerosols to scatter radiation and hence impact upon visibility. The dependence of visibility on other meteorological parameters (e.g. relative humidity, air temperature, wind speed & direction) is also investigated. To explain the long term visibility trends and their dependence on meteorological conditions, a light extinction model was constructed incorporating the concentrations and composition of historic aerosol. The lack of historic aerosol size distributions and aerosol composition data, which determine hygroscopicity and refractive index, leads to an under-constrained model. Aerosol measurements from the last 10 years are used to constrain these model parameters, and hence their historical variation can be estimated; sensitivity analyses are used to estimate errors for the time period before regular aerosol measurements are available. A good agreement is observed between modelled and measured visibility. This work has generated a unique 60 year data set with which to understand how aerosol concentration and composition has varied over the UK. The model is applicable and easily transferrable to other data sets worldwide. Hence, different clean air legislation can be assessed for its effectiveness in reducing aerosol pollution. The implications for the UK will be discussed.

Propagation of radar rainfall uncertainty in urban flood simulations

NASA Astrophysics Data System (ADS)

Liguori, Sara; Rico-Ramirez, Miguel

2013-04-01

This work discusses the results of the implementation of a novel probabilistic system designed to improve ensemble sewer flow predictions for the drainage network of a small urban area in the North of England. The probabilistic system has been developed to model the uncertainty associated to radar rainfall estimates and propagate it through radar-based ensemble sewer flow predictions. The assessment of this system aims at outlining the benefits of addressing the uncertainty associated to radar rainfall estimates in a probabilistic framework, to be potentially implemented in the real-time management of the sewer network in the study area. Radar rainfall estimates are affected by uncertainty due to various factors [1-3] and quality control and correction techniques have been developed in order to improve their accuracy. However, the hydrological use of radar rainfall estimates and forecasts remains challenging. A significant effort has been devoted by the international research community to the assessment of the uncertainty propagation through probabilistic hydro-meteorological forecast systems [4-5], and various approaches have been implemented for the purpose of characterizing the uncertainty in radar rainfall estimates and forecasts [6-11]. A radar-based ensemble stochastic approach, similar to the one implemented for use in the Southern-Alps by the REAL system [6], has been developed for the purpose of this work. An ensemble generator has been calibrated on the basis of the spatial-temporal characteristics of the residual error in radar estimates assessed with reference to rainfall records from around 200 rain gauges available for the year 2007, previously post-processed and corrected by the UK Met Office [12-13]. Each ensemble member is determined by summing a perturbation field to the unperturbed radar rainfall field. The perturbations are generated by imposing the radar error spatial and temporal correlation structure to purely stochastic fields. A hydrodynamic sewer network model implemented in the Infoworks software was used to model the rainfall-runoff process in the urban area. The software calculates the flow through the sewer conduits of the urban model using rainfall as the primary input. The sewer network is covered by 25 radar pixels with a spatial resolution of 1 km2. The majority of the sewer system is combined, carrying both urban rainfall runoff as well as domestic and trade waste water [11]. The urban model was configured to receive the probabilistic radar rainfall fields. The results showed that the radar rainfall ensembles provide additional information about the uncertainty in the radar rainfall measurements that can be propagated in urban flood modelling. The peaks of the measured flow hydrographs are often bounded within the uncertainty area produced by using the radar rainfall ensembles. This is in fact one of the benefits of using radar rainfall ensembles in urban flood modelling. More work needs to be done in improving the urban models, but this is out of the scope of this research. The rainfall uncertainty cannot explain the whole uncertainty shown in the flow simulations, and additional sources of uncertainty will come from the structure of the urban models as well as the large number of parameters required by these models. Acknowledgements The authors would like to acknowledge the BADC, the UK Met Office and the UK Environment Agency for providing the various data sets. We also thank Yorkshire Water Services Ltd for providing the urban model. The authors acknowledge the support from the Engineering and Physical Sciences Research Council (EPSRC) via grant EP/I012222/1. References [1] Browning KA, 1978. Meteorological applications of radar. Reports on Progress in Physics 41 761 Doi: 10.1088/0034-4885/41/5/003 [2] Rico-Ramirez MA, Cluckie ID, Shepherd G, Pallot A, 2007. A high-resolution radar experiment on the island of Jersey. Meteorological Applications 14: 117-129. [3] Villarini G, Krajewski WF, 2010. Review of the different sources of uncertainty in single polarization radar-based estimates of rainfall. Surveys in Geophysics 31: 107-129. [4] Rossa A, Liechti K, Zappa M, Bruen M, Germann U, Haase G, Keil C, Krahe P, 2011. The COST 731 Action: A review on uncertainty propagation in advanced hydrometeorological forecast systems. Atmospheric Research 100, 150-167. [5] Rossa A, Bruen M, Germann U, Haase G, Keil C, Krahe P, Zappa M, 2010. Overview and Main Results on the interdisciplinary effort in flood forecasting COST 731-Propagation of Uncertainty in Advanced Meteo-Hydrological Forecast Systems. Proceedings of Sixth European Conference on Radar in Meteorology and Hydrology ERAD 2010. [6] Germann U, Berenguer M, Sempere-Torres D, Zappa M, 2009. REAL - ensemble radar precipitation estimation for hydrology in a mountainous region. Quarterly Journal of the Royal Meteorological Society 135: 445-456. [8] Bowler NEH, Pierce CE, Seed AW, 2006. STEPS: a probabilistic precipitation forecasting scheme which merges and extrapolation nowcast with downscaled NWP. Quarterly Journal of the Royal Meteorological Society 132: 2127-2155. [9] Zappa M, Rotach MW, Arpagaus M, Dorninger M, Hegg C, Montani A, Ranzi R, Ament F, Germann U, Grossi G et al., 2008. MAP D-PHASE: real-time demonstration of hydrological ensemble prediction systems. Atmospheric Science Letters 9, 80-87. [10] Liguori S, Rico-Ramirez MA. Quantitative assessment of short-term rainfall forecasts from radar nowcasts and MM5 forecasts. Hydrological Processes, accepted article. DOI: 10.1002/hyp.8415 [11] Liguori S, Rico-Ramirez MA, Schellart ANA, Saul AJ, 2012. Using probabilistic radar rainfall nowcasts and NWP forecasts for flow prediction in urban catchments. Atmospheric Research 103: 80-95. [12] Harrison DL, Driscoll SJ, Kitchen M, 2000. Improving precipitation estimates from weather radar using quality control and correction techniques. Meteorological Applications 7: 135-144. [13] Harrison DL, Scovell RW, Kitchen M, 2009. High-resolution precipitation estimates for hydrological uses. Proceedings of the Institution of Civil Engineers - Water Management 162: 125-135.

An inter-model comparison of urban canopy effects on climate

NASA Astrophysics Data System (ADS)

Halenka, Tomas; Karlicky, Jan; Huszar, Peter; Belda, Michal; Bardachova, Tatsiana

2017-04-01

The role of cities is increasing and will continue to increase in future, as the population within the urban areas is growing faster, with the estimate for Europe of about 84% living in urban areas in about mid of 21st century. To assess the impact of cities and, in general, urban surfaces on climate, using of modeling approach is well appropriate. Moreover, with higher resolution, urban areas becomes to be better resolved in the regional models and their relatively significant impacts should not be neglected. Model descriptions of urban canopy related meteorological effects can, however, differ largely given the odds in the driving models, the underlying surface models and the urban canopy parameterizations, representing a certain uncertainty. In this study we try to contribute to the estimation of this uncertainty by performing numerous experiments to assess the urban canopy meteorological forcing over central Europe on climate for the decade 2001-2010, using two driving models (RegCM4 and WRF) in 10 km resolution driven by ERA-Interim reanalyses, three surface schemes (BATS and CLM4.5 for RegCM4 and Noah for WRF) and five urban canopy parameterizations available: one bulk urban scheme, three single layer and a multilayer urban scheme. Actually, in RegCM4 we used our implementation of the Single Layer Urban Canopy Model (SLUCM) in BATS scheme and CLM4.5 option with urban parameterization based on SLUCM concept as well, in WRF we used all the three options, i.e. bulk, SLUCM and more complex and sophisticated Building Environment Parameterization (BEP) connected with Building Energy Model (BEM). As a reference simulations, runs with no urban areas and with no urban parameterizations were performed. Effects of cities on urban and rural areas were evaluated. Effect of reducing diurnal temperature range in cities (around 2 °C in summer) is noticeable in all simulation, independent to urban parameterization type and model. Also well-known warmer summer city nights appear in all simulations. Further, winter boundary layer increase by 100-200 m, together with wind reduction, is visible in all simulations. The spatial distribution of the night-time temperature response of models to urban canopy forcing is rather similar in each set-up, showing temperature increases up to 3°C in summer. In general, much lower increase are modeled for day-time conditions, which can be even slightly negative due to dominance of shadowing in urban canyons, especially in the morning hours. The winter temperature response, driven mainly by anthropogenic heat (AH) is strong in urban schemes where the building-street energy exchange is more resolved and is smaller, where AH is simply prescribed as additive flux to the sensible heat. Somewhat larger differences between the models are encountered for the response of wind and the height of planetary boundary layer (ZPBL), with dominant increases from a few 10 m up to 250 m depending on the model. The comparison of observation of diurnal temperature amplitude from ECAD data with model results and hourly data from Prague with model hourly values show improvement when urban effects are considered. Larger spread encountered for wind and turbulence (as ZPBL) should be considered when choices of urban canopy schemes are made, especially in connection with modeling transport of pollutants within/from cities. Another conclusion is that choosing more complex urban schemes does not necessary improves model performance and using simpler and computationally less demanding (e.g. single layer) urban schemes, is often sufficient.

The role of local urban traffic and meteorological conditions in air pollution: A data-based case study in Madrid, Spain

NASA Astrophysics Data System (ADS)

Laña, Ibai; Del Ser, Javier; Padró, Ales; Vélez, Manuel; Casanova-Mateo, Carlos

2016-11-01

Urban air pollution is a matter of growing concern for both public administrations and citizens. Road traffic is one of the main sources of air pollutants, though topography characteristics and meteorological conditions can make pollution levels increase or diminish dramatically. In this context an upsurge of research has been conducted towards functionally linking variables of such domains to measured pollution data, with studies dealing with up to one-hour resolution meteorological data. However, the majority of such reported contributions do not deal with traffic data or, at most, simulate traffic conditions jointly with the consideration of different topographical features. The aim of this study is to further explore this relationship by using high-resolution real traffic data. This paper describes a methodology based on the construction of regression models to predict levels of different pollutants (i.e. CO, NO, NO2, O3 and PM10) based on traffic data and meteorological conditions, from which an estimation of the predictive relevance (importance) of each utilized feature can be estimated by virtue of their particular training procedure. The study was made with one hour resolution meteorological, traffic and pollution historic data in roadside and background locations of the city of Madrid (Spain) captured over 2015. The obtained results reveal that the impact of vehicular emissions on the pollution levels is overshadowed by the effects of stable meteorological conditions of this city.

INTRODUCTION OF URBAN CANOPY PARAMETERIZATION INTO MM5 TO SIMULATE URBAN METEOROLOGY AT NEIGHBORHOOD SCALE

EPA Science Inventory

Since most of the primary atmospheric pollutants are emitted inside the roughness sub-layer (RSL) and consequently the first chemical reactions and dispersion occur in this layer, it is necessary to generate detailed meteorological fields inside the RSL to perform air quality m...

Effect modification of the association between short-term meteorological factors and mortality by urban heat islands in Hong Kong.

PubMed

Goggins, William B; Chan, Emily Y Y; Ng, Edward; Ren, Chao; Chen, Liang

2012-01-01

Prior studies from around the world have indicated that very high temperatures tend to increase summertime mortality. However possible effect modification by urban micro heat islands has only been examined by a few studies in North America and Europe. This study examined whether daily mortality in micro heat island areas of Hong Kong was more sensitive to short term changes in meteorological conditions than in other areas. An urban heat island index (UHII) was calculated for each of Hong Kong's 248 geographical tertiary planning units (TPU). Daily counts of all natural deaths among Hong Kong residents were stratified according to whether the place of residence of the decedent was in a TPU with high (above the median) or low UHII. Poisson Generalized Additive Models (GAMs) were used to estimate the association between meteorological variables and mortality while adjusting for trend, seasonality, pollutants and flu epidemics. Analyses were restricted to the hot season (June-September). Mean temperatures (lags 0-4) above 29 °C and low mean wind speeds (lags 0-4) were significantly associated with higher daily mortality and these associations were stronger in areas with high UHII. A 1 °C rise above 29 °C was associated with a 4.1% (95% confidence interval (CI): 0.7%, 7.6%) increase in natural mortality in areas with high UHII but only a 0.7% (95% CI: -2.4%, 3.9%) increase in low UHII areas. Lower mean wind speeds (5(th) percentile vs. 95(th) percentile) were associated with a 5.7% (95% CI: 2.7, 8.9) mortality increase in high UHII areas vs. a -0.3% (95% CI: -3.2%, 2.6%) change in low UHII areas. The results suggest that urban micro heat islands exacerbate the negative health consequences of high temperatures and low wind speeds. Urban planning measures designed to mitigate heat island effects may lessen the health effects of unfavorable summertime meteorological conditions.

Photochemical modeling and analysis of meteorological parameters during ozone episodes in Kaohsiung, Taiwan

NASA Astrophysics Data System (ADS)

Chen, K. S.; Ho, Y. T.; Lai, C. H.; Chou, Youn-Min

The events of high ozone concentrations and meteorological conditions covering the Kaohsiung metropolitan area were investigated based on data analysis and model simulation. A photochemical grid model was employed to analyze two ozone episodes in autumn (2000) and winter (2001) seasons, each covering three consecutive days (or 72 h) in the Kaohsiung City. The potential influence of the initial and boundary conditions on model performance was assessed. Model performance can be improved by separately considering the daytime and nighttime ozone concentrations on the lateral boundary conditions of the model domain. The sensitivity analyses of ozone concentrations to the emission reductions in volatile organic compounds (VOC) and nitrogen oxides (NO x) show a VOC-sensitive regime for emission reductions to lower than 30-40% VOC and 30-50% NO x and a NO x-sensitive regime for larger percentage reductions. Meteorological parameters show that warm temperature, sufficient sunlight, low wind, and high surface pressure are distinct parameters that tend to trigger ozone episodes in polluted urban areas, like Kaohsiung.

60 years of visibility data in the UK - how does visibility vary with meteorological and pollutant parameters?

NASA Astrophysics Data System (ADS)

Singh, A.; Bloss, W.; Pope, F.

2015-12-01

Reduced visibility can be an indicator of poor air quality. Moreover, degradation in visibility can be hazardous to human safety; for example, low visibility can lead to accidents particularly during the winter season when fogs are prevalent. Here, we explore the combined influence of aerosol characteristics and meteorology on long-term visibility. We use visibility data from eight meteorological stations, situated in the UK, which have been running since the 1950s. The site locations include urban, rural and marine environments. Most stations show a long term trend of visibility increase, which is indicative of reductions in aerosol pollution, especially in urban areas. Additionally, results at all sites show a very clear dependence on relative humidity, indicating the importance of aerosol hygroscopicity on the ability of aerosols to scatter radiation and hence impact upon visibility. The dependence of visibility on other meteorological parameters (e.g. wind speed, wind direction) is also investigated. To explain the long term visibility trends and their dependence on meteorological conditions, a light extinction model was constructed incorporating the concentrations and composition of historic aerosol. The lack of historic aerosol size distributions and aerosol composition data, which determine hygroscopicity and refractive index, leads to an under-constrained model. Aerosol measurements from the last 10 years are used to constrain these model parameters, and hence their historical variation can be estimated; sensitivity analyses are used to estimate errors for the time period before regular aerosol measurements are available. This work has generated a unique 60 year data set with which to understand how aerosol concentration and composition has varied over the UK. The model is applicable and easily transferrable to other data sets worldwide. Hence, different clean air legislation can be assessed for its effectiveness in reducing aerosol pollution. The implications for the UK will be discussed.

The value of using seasonality and meteorological variables to model intra-urban PM2.5 variation

NASA Astrophysics Data System (ADS)

Olvera Alvarez, Hector A.; Myers, Orrin B.; Weigel, Margaret; Armijos, Rodrigo X.

2018-06-01

A yearlong air monitoring campaign was conducted to assess the impact of local temperature, relative humidity, and wind speed on the temporal and spatial variability of PM2.5 in El Paso, Texas. Monitoring was conducted at four sites purposely selected to capture the local traffic variability. Effects of meteorological events on seasonal PM2.5 variability were identified. For instance, in winter low-wind and low-temperature conditions were associated with high PM2.5 events that contributed to elevated seasonal PM2.5 levels. Similarly, in spring, high PM2.5 events were associated with high-wind and low-relative humidity conditions. Correlation coefficients between meteorological variables and PM2.5 fluctuated drastically across seasons. Specifically, it was observed that for most sites correlations between PM2.5 and meteorological variables either changed from positive to negative or dissolved depending on the season. Overall, the results suggest that mixed effects analysis with season and site as fixed factors and meteorological variables as covariates could increase the explanatory value of LUR models for PM2.5.

Conjunctively optimizing flash flood control and water quality in urban water reservoirs by model predictive control and dynamic emulation

NASA Astrophysics Data System (ADS)

Galelli, Stefano; Goedbloed, Albert; Schmitter, Petra; Castelletti, Andrea

2014-05-01

Urban water reservoirs are a viable adaptation option to account for increasing drinking water demand of urbanized areas as they allow storage and re-use of water that is normally lost. In addition, the direct availability of freshwater reduces pumping costs and diversifies the portfolios of drinking water supply. Yet, these benefits have an associated twofold cost. Firstly, the presence of large, impervious areas increases the hydraulic efficiency of urban catchments, with short time of concentration, increased runoff rates, losses of infiltration and baseflow, and higher risk of flash floods. Secondly, the high concentration of nutrients and sediments characterizing urban discharges is likely to cause water quality problems. In this study we propose a new control scheme combining Model Predictive Control (MPC), hydro-meteorological forecasts and dynamic model emulation to design real-time operating policies that conjunctively optimize water quantity and quality targets. The main advantage of this scheme stands in its capability of exploiting real-time hydro-meteorological forecasts, which are crucial in such fast-varying systems. In addition, the reduced computational requests of the MPC scheme allows coupling it with dynamic emulators of water quality processes. The approach is demonstrated on Marina Reservoir, a multi-purpose reservoir located in the heart of Singapore and characterized by a large, highly urbanized catchment with a short (i.e. approximately one hour) time of concentration. Results show that the MPC scheme, coupled with a water quality emulator, provides a good compromise between different operating objectives, namely flood risk reduction, drinking water supply and salinity control. Finally, the scheme is used to assess the effect of source control measures (e.g. green roofs) aimed at restoring the natural hydrological regime of Marina Reservoir catchment.

Urban heat island research from 1991 to 2015: a bibliometric analysis

NASA Astrophysics Data System (ADS)

Huang, Qunfang; Lu, Yuqi

2018-02-01

A bibliometric analysis based on the Science Citation Index-Expanded (SCI-Expanded) database from the Web of Science was performed to review urban heat island (UHI) research from 1991 to 2015 and statistically assess its developments, trends, and directions. In total, 1822 papers published in 352 journals over the past 25 years were analyzed for scientific output; citations; subject categories; major journals; outstanding keywords; and leading countries, institutions, authors, and research collaborations. The number of UHI-related publications has continuously increased since 1991. Meteorology atmospheric sciences, environmental sciences, and construction building technology were the three most frequent subject categories. Building and Environment, International Journal of Climatology, and Theoretical and Applied Climatology were the three most popular publishing journals. The USA and China were the two leading countries in UHI research, contributing 49.56% of the total articles. Chinese Academy of Science, Arizona State University, and China Meteorological Administration published the most UHI articles. Weng QH and Santamouris M were the two most prolific authors. Author keywords were classified into four major groups: (1) research methods and indicators, e.g., remote sensing, field measurement, and models; (2) generation factors, e.g., impervious urban surfaces, urban geometry, waste heat, vegetation, and pollutants; (3) environmental effects, e.g., urban climate, heat wave, ecology, and pollution; and (4) mitigation and adaption strategies, e.g., roof technology cooling, reflective cooling, vegetation cooling, and urban geometry cooling. A comparative analysis of popular issues revealed that UHI determination (intensity, heat source, supporting techniques) remains the central topic, whereas UHI impacts and mitigation strategies are becoming the popular issues that will receive increasing scientific attention in the future. Modeling will continue to be the leading research method, and remote sensing will be used more widely. Additionally, a combination of remote sensing and field measurements with models is expected.

Crowdsourcing urban air temperatures through smartphone battery temperatures in São Paulo, Brazil

NASA Astrophysics Data System (ADS)

Droste, Arjan; Pape, Jan-Jaap; Overeem, Aart; Leijnse, Hidde; Steeneveld, Gert-Jan; Van Delden, Aarnout; Uijlenhoet, Remko

2017-04-01

Crowdsourcing as a method to obtain and apply vast datasets is rapidly becoming prominent in meteorology, especially for urban areas where traditional measurements are scarce. Earlier studies showed that smartphone battery temperature readings allow for estimating the daily and city-wide air temperature via a straightforward heat transfer model. This study advances these model estimations by studying spatially and temporally smaller scales. The accuracy of temperature retrievals as a function of the number of battery readings is also studied. An extensive dataset of over 10 million battery temperature readings is available for São Paulo (Brazil), for estimating hourly and daily air temperatures. The air temperature estimates are validated with air temperature measurements from a WMO station, an Urban Fluxnet site, and crowdsourced data from 7 hobby meteorologists' private weather stations. On a daily basis temperature estimates are good, and we show they improve by optimizing model parameters for neighbourhood scales as categorized in Local Climate Zones. Temperature differences between Local Climate Zones can be distinguished from smartphone battery temperatures. When validating the model for hourly temperature estimates, initial results are poor, but are vastly improved by using a diurnally varying parameter function in the heat transfer model rather than one fixed value for the entire day. The obtained results show the potential of large crowdsourced datasets in meteorological studies, and the value of smartphones as a measuring platform when routine observations are lacking.

Sub-kilometer Numerical Weather Prediction in complex urban areas

NASA Astrophysics Data System (ADS)

Leroyer, S.; Bélair, S.; Husain, S.; Vionnet, V.

2013-12-01

A Sub-kilometer atmospheric modeling system with grid-spacings of 2.5 km, 1 km and 250 m and including urban processes is currently being developed at the Meteorological Service of Canada (MSC) in order to provide more accurate weather forecasts at the city scale. Atmospheric lateral boundary conditions are provided with the 15-km Canadian Regional Deterministic Prediction System (RDPS). Surface physical processes are represented with the Town Energy Balance (TEB) model for the built-up covers and with the Interactions between the Surface, Biosphere, and Atmosphere (ISBA) land surface model for the natural covers. In this study, several research experiments over large metropolitan areas and using observational networks at the urban scale are presented, with a special emphasis on the representation of local atmospheric circulations and their impact on extreme weather forecasting. First, numerical simulations are performed over the Vancouver metropolitan area during a summertime Intense Observing Period (IOP of 14-15 August 2008) of the Environmental Prediction in Canadian Cities (EPiCC) observational network. The influence of the horizontal resolution on the fine-scale representation of the sea-breeze development over the city is highlighted (Leroyer et al., 2013). Then severe storms cases occurring in summertime within the Greater Toronto Area (GTA) are simulated. In view of supporting the 2015 PanAmerican and Para-Pan games to be hold in GTA, a dense observational network has been recently deployed over this region to support model evaluations at the urban and meso scales. In particular, simulations are conducted for the case of 8 July 2013 when exceptional rainfalls were recorded. Leroyer, S., S. Bélair, J. Mailhot, S.Z. Husain, 2013: Sub-kilometer Numerical Weather Prediction in an Urban Coastal Area: A case study over the Vancouver Metropolitan Area, submitted to Journal of Applied Meteorology and Climatology.

Investigation of the climate change within Moscow metropolitan area

NASA Astrophysics Data System (ADS)

Varentsov, Mikhail; Trusilova, Kristina; Konstantinov, Pavel; Samsonov, Timofey

2014-05-01

As the urbanization continues worldwide more than half of the Earth's population live in the cities (U.N., 2010). Therefore the vulnerability of the urban environment - the living space for millions of people - to the climate change has to be investigated. It is well known that urban features strongly influence the atmospheric boundary layer and determine the microclimatic features of the local environment, such as urban heat island (UHI). Available temperature observations in cities are, however, influenced by the natural climate variations, human-induced climate warming (IPCC, 2007) and in the same time by the growth and structural modification of the urban areas. The relationship between these three factors and their roles in climate changes in the cities are very important for the climatic forecast and requires better understanding. In this study, we made analysis of the air temperature change and urban heat island evolution within Moscow urban area during decades 1970-2010, while this urban area had undergone intensive growth and building modification allowing the population of Moscow to increase from 7 to 12 million people. Analysis was based on the data from several meteorological stations in Moscow region and Moscow city, including meteorological observatory of Lomonosov Moscow State University. Differences in climate change between urban and rural stations, changes of the power and shape of urban heat island and their relationships with changes of building height and density were investigated. Collected data and obtained results are currently to be used for the validation of the regional climate model COSMO-CLM with the purpose to use this model for further more detailed climate research and forecasts for Moscow metropolitan area. References: 1. U.N. (2010), World Urbanization Prospects. The 2009 Revision.Rep., 1-47 pp, United Nations. Department of Economic and Social Affairs. Population Division., New York. 2. IPCC (2007), IPCC Fourth Assessment Report: Climate Change 2007 (AR4) Rep.,Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

NOAA Atmospheric Sciences Modeling Division support to the US Environmental Protection Agency

NASA Astrophysics Data System (ADS)

Poole-Kober, Evelyn M.; Viebrock, Herbert J.

1991-07-01

During FY-1990, the Atmospheric Sciences Modeling Division provided meteorological research and operational support to the U.S. Environmental Protection Agency. Basic meteorological operational support consisted of applying dispersion models and conducting dispersion studies and model evaluations. The primary research effort was the development and evaluation of air quality simulation models using numerical and physical techniques supported by field studies. Modeling emphasis was on the dispersion of photochemical oxidants and particulate matter on urban and regional scales, dispersion in complex terrain, and the transport, transformation, and deposition of acidic materials. Highlights included expansion of the Regional Acid Deposition Model/Engineering Model family to consist of the Tagged Species Engineering Model, the Non-Depleting Model, and the Sulfate Tracking Model; completion of the Acid-MODES field study; completion of the RADM2.1 evaluation; completion of the atmospheric processes section of the National Acid Precipitation Assessment Program 1990 Integrated Assessment; conduct of the first field study to examine the transport and entrainment processes of convective clouds; development of a Regional Oxidant Model-Urban Airshed Model interface program; conduct of an international sodar intercomparison experiment; incorporation of building wake dispersion in numerical models; conduct of wind-tunnel simulations of stack-tip downwash; and initiation of the publication of SCRAM NEWS.

High resolution urban morphology data for urban wind flow modeling

NASA Astrophysics Data System (ADS)

Cionco, Ronald M.; Ellefsen, Richard

The application of urban forestry methods and technologies to a number of practical problems can be further enhanced by the use and incorporation of localized, high resolution wind and temperature fields into their analysis methods. The numerical simulation of these micrometeorological fields will represent the interactions and influences of urban structures, vegetation elements, and variable terrain as an integral part of the dynamics of an urban domain. Detailed information of the natural and man-made components that make up the urban area is needed to more realistically model meteorological fields in urban domains. Simulating high resolution wind and temperatures over and through an urban domain utilizing detailed morphology data can also define and quantify local areas where urban forestry applications can contribute to better solutions. Applications such as the benefits of planting trees for shade purposes can be considered, planned, and evaluated for their impact on conserving energy and cooling costs as well as the possible reconfiguration or removal of trees and other barriers for improved airflow ventilation and similar processes. To generate these fields, a wind model must be provided, as a minimum, the location, type, height, structural silhouette, and surface roughness of these components, in order to account for the presence and effects of these land morphology features upon the ambient airflow. The morphology of Sacramento, CA has been characterized and quantified in considerable detail primarily for wind flow modeling, simulation, and analyses, but can also be used for improved meteorological analyses, urban forestry, urban planning, and other urban related activities. Morphology methods previously developed by Ellefsen are applied to the Sacramento scenario with a high resolution grid of 100 m × 100 m. The Urban Morphology Scheme defines Urban Terrain Zones (UTZ) according to how buildings and other urban elements are structured and placed with respect to each other. The urban elements within the 100 m × 100 m cells (one hectare) are further described and digitized as building height, building footprint (in percent), reflectivity of its roof, pitched roof or flat, building's long axis orientation, footprint of impervious surface and its reflectivity, footprint of canopy elements, footprint of woodlots, footprint of grass area, and footprint of water surface. A variety of maps, satellite images, low level aerial photographs, and street level photographs are the raw data used to quantify these urban properties. The final digitized morphology database resides in a spreadsheet ready for use on ordinary personal computers.

A study of model parameters associated with the urban climate using HCMM data. [St. Louis, Missouri

NASA Technical Reports Server (NTRS)

1981-01-01

The use of infrared and visible data from the Heat Capacity Mapping Mission (HCMM) and in situ data to study the intensity of the urban heat island of Saint Louis is described. Analysis of HCMM data shows that an urban heat island exists day and night in all seasons when clear skies prevail. The lower albedo value of the urban region during the day suggests that the higher temperatures are due to more absorption of solar radiation. Preliminary analysis of in situ meteorological data was performed after merging with HCMM data, and surface roughness, the exchange coefficient, and the soil moisture were calculated.

Performance assessment of retrospective meteorological inputs for use in air quality modeling during TexAQS 2006

NASA Astrophysics Data System (ADS)

Ngan, Fong; Byun, Daewon; Kim, Hyuncheol; Lee, Daegyun; Rappenglück, Bernhard; Pour-Biazar, Arastoo

2012-07-01

To achieve more accurate meteorological inputs than was used in the daily forecast for studying the TexAQS 2006 air quality, retrospective simulations were conducted using objective analysis and 3D/surface analysis nudging with surface and upper observations. Model ozone using the assimilated meteorological fields with improved wind fields shows better agreement with the observation compared to the forecasting results. In the post-frontal conditions, important factors for ozone modeling in terms of wind patterns are the weak easterlies in the morning for bringing in industrial emissions to the city and the subsequent clockwise turning of the wind direction induced by the Coriolis force superimposing the sea breeze, which keeps pollutants in the urban area. Objective analysis and nudging employed in the retrospective simulation minimize the wind bias but are not able to compensate for the general flow pattern biases inherited from large scale inputs. By using an alternative analyses data for initializing the meteorological simulation, the model can re-produce the flow pattern and generate the ozone peak location closer to the reality. The inaccurate simulation of precipitation and cloudiness cause over-prediction of ozone occasionally. Since there are limitations in the meteorological model to simulate precipitation and cloudiness in the fine scale domain (less than 4-km grid), the satellite-based cloud is an alternative way to provide necessary inputs for the retrospective study of air quality.

A real-time control framework for urban water reservoirs operation

NASA Astrophysics Data System (ADS)

Galelli, S.; Goedbloed, A.; Schwanenberg, D.

2012-04-01

Drinking water demand in urban areas is growing parallel to the worldwide urban population, and it is acquiring an increasing part of the total water consumption. Since the delivery of sufficient water volumes in urban areas represents a difficult logistic and economical problem, different metropolitan areas are evaluating the opportunity of constructing relatively small reservoirs within urban areas. Singapore, for example, is developing the so-called 'Four National Taps Strategies', which detects the maximization of water yields from local, urban catchments as one of the most important water sources. However, the peculiar location of these reservoirs can provide a certain advantage from the logistical point of view, but it can pose serious difficulties in their daily management. Urban catchments are indeed characterized by large impervious areas: this results in a change of the hydrological cycle, with decreased infiltration and groundwater recharge, and increased patterns of surface and river discharges, with higher peak flows, volumes and concentration time. Moreover, the high concentrations of nutrients and sediments characterizing urban discharges can cause further water quality problems. In this critical hydrological context, the effective operation of urban water reservoirs must rely on real-time control techniques, which can exploit hydro-meteorological information available in real-time from hydrological and nowcasting models. This work proposes a novel framework for the real-time control of combined water quality and quantity objectives in urban reservoirs. The core of this framework is a non-linear Model Predictive Control (MPC) scheme, which employs the current state of the system, the future discharges furnished by a predictive model and a further model describing the internal dynamics of the controlled sub-system to determine an optimal control sequence over a finite prediction horizon. The main advantage of this scheme stands in its reduced computational requests and the capability of exploiting real-time hydro-meteorological information, which are crucial for an effective operation of these fast-varying hydrological systems. The framework is here demonstrated on the operation of Marina Reservoir (Singapore), whose recent construction in late 2008 increased the effective catchment area to about 50% of the total available. Its operation, which accounts for drinking water supply, flash floods control and water quality standards, is here designed by combining the MPC scheme with the process-based hydrological model SOBEK. Extensive simulation experiments show the validity of the proposed framework.

Comparison between the Community Land Model and the Terra Urb model in COSMO 5.0 over tropical Africa

NASA Astrophysics Data System (ADS)

Brousse, Oscar; Wouters, Hendrik; Thiery, Wim; Demuzere, Matthias; Van Lipzig, Nicole

2017-04-01

African urban inhabitants are expected to rise up to 75% of the continent's population at the horizon of 2050 (United Nations, 2014). This unprecedented demographic rise has led to an uncontrolled urbanization, and hence to a lack of public health infrastructures and administration within African cities. During the past decades, as an example, malaria's mitigating infrastructures have been constructed without considering the impact of urbanization. Indexes of malaria's risks have been based on rural areas, driving huge biases by not taking into account characteristics of the urban environment. In response to this challenge, the REACT project sets out to develop an index for malaria risk in urban tropical Africa. In particular, we aim to create two indexes that apply to the regional and local scale, respectively. Especially, intra-urban variability of the near-surface climate and the malaria's epidemiology thus needs to be described. To start, we first conduct a series of sensitivity simulations over a one-year period to determine which Land Surface Model (LSM) implemented within COSMO 5.0 is most suited for the purpose of this research. The model domain will cover the Lake Victoria area, integrating Kampala within its boundaries. The regional climate is considered as tropical and interactions between Lake Victoria and its surroundings have been proven (Thiery et al., 2015; 2016). Since malaria depends on typical meteorological and climatic factors such as precipitation, relative humidity, wind speed and temperature, the first part of the project aims at finding which of the LSMs able to assess the more conveniently those epidemiological drivers. Indeed, the results of those runs will serve both the scales for inter- and intra-urban analysis (through a downscaling approach) and hence need to be as detailed as possible. The coupling of COSMO-CLM with the Community Land Model (COSMO-CLM2; Davin and Seneviratne, 2012) is known to have a better integration of vegetation's influence on the meteorological circulations, while the COSMO-CLM coupled with the TerraUrb Urban Canopy Model (Wouters et al., 2015; 2016) is evaluated to have a robust representation of the urban areas' interactions with the atmosphere. Both couplings will be subject to the same boundary conditions and period of study before being compared with a reference run, only vegetated, performed with the COSMO-CLM2, and with a suite of observational products.

Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe - Part 1: Model description and evaluation of meteorological predictions

NASA Astrophysics Data System (ADS)

Zhang, Y.; Sartelet, K.; Wu, S.-Y.; Seigneur, C.

2013-02-01

Comprehensive model evaluation and comparison of two 3-D air quality modeling systems (i.e. the Weather Research and Forecast model (WRF)/Polyphemus and WRF with chemistry and the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) (WRF/Chem-MADRID) are conducted over western Europe. Part 1 describes the background information for the model comparison and simulation design, as well as the application of WRF for January and July 2001 over triple-nested domains in western Europe at three horizontal grid resolutions: 0.5°, 0.125°, and 0.025°. Six simulated meteorological variables (i.e. temperature at 2 m (T2), specific humidity at 2 m (Q2), relative humidity at 2 m (RH2), wind speed at 10 m (WS10), wind direction at 10 m (WD10), and precipitation (Precip)) are evaluated using available observations in terms of spatial distribution, domainwide daily and site-specific hourly variations, and domainwide performance statistics. WRF demonstrates its capability in capturing diurnal/seasonal variations and spatial gradients of major meteorological variables. While the domainwide performance of T2, Q2, RH2, and WD10 at all three grid resolutions is satisfactory overall, large positive or negative biases occur in WS10 and Precip even at 0.025°. In addition, discrepancies between simulations and observations exist in T2, Q2, WS10, and Precip at mountain/high altitude sites and large urban center sites in both months, in particular, during snow events or thunderstorms. These results indicate the model's difficulty in capturing meteorological variables in complex terrain and subgrid-scale meteorological phenomena, due to inaccuracies in model initialization parameterization (e.g. lack of soil temperature and moisture nudging), limitations in the physical parameterizations of the planetary boundary layer (e.g. cloud microphysics, cumulus parameterizations, and ice nucleation treatments) as well as limitations in surface heat and moisture budget parameterizations (e.g. snow-related processes, subgrid-scale surface roughness elements, and urban canopy/heat island treatments and CO2 domes). While the use of finer grid resolutions of 0.125° and 0.025° shows some improvement for WS10, Precip, and some mesoscale events (e.g. strong forced convection and heavy precipitation), it does not significantly improve the overall statistical performance for all meteorological variables except for Precip. These results indicate a need to further improve the model representations of the above parameterizations at all scales.

Can Aerosol Offset Urban Heat Island Effect?

NASA Astrophysics Data System (ADS)

Jin, M. S.; Shepherd, J. M.

2009-12-01

The Urban Heat Island effect (UHI) refers to urban skin or air temperature exceeding the temperatures in surrounding non-urban regions. In a warming climate, the UHI may intensify extreme heat waves and consequently cause significant health and energy problems. Aerosols reduce surface insolation via the direct effect, namely, scattering and absorbing sunlight in the atmosphere. Combining the National Aeronautics and Space Administration (NASA) AERONET (AErosol RObotic NETwork) observations over large cities together with Weather Research and Forecasting Model (WRF) simulations, we find that the aerosol direct reduction of surface insolation range from 40-100 Wm-2, depending on seasonality and aerosol loads. As a result, surface skin temperature can be reduced by 1-2C while 2-m surface air temperature by 0.5-1C. This study suggests that the aerosol direct effect is a competing mechanism for the urban heat island effect (UHI). More importantly, both aerosol and urban land cover effects must be adequately represented in meteorological and climate modeling systems in order to properly characterize urban surface energy budgets and UHI.

Random forest meteorological normalisation models for Swiss PM10 trend analysis

NASA Astrophysics Data System (ADS)

Grange, Stuart K.; Carslaw, David C.; Lewis, Alastair C.; Boleti, Eirini; Hueglin, Christoph

2018-05-01

Meteorological normalisation is a technique which accounts for changes in meteorology over time in an air quality time series. Controlling for such changes helps support robust trend analysis because there is more certainty that the observed trends are due to changes in emissions or chemistry, not changes in meteorology. Predictive random forest models (RF; a decision tree machine learning technique) were grown for 31 air quality monitoring sites in Switzerland using surface meteorological, synoptic scale, boundary layer height, and time variables to explain daily PM10 concentrations. The RF models were used to calculate meteorologically normalised trends which were formally tested and evaluated using the Theil-Sen estimator. Between 1997 and 2016, significantly decreasing normalised PM10 trends ranged between -0.09 and -1.16 µg m-3 yr-1 with urban traffic sites experiencing the greatest mean decrease in PM10 concentrations at -0.77 µg m-3 yr-1. Similar magnitudes have been reported for normalised PM10 trends for earlier time periods in Switzerland which indicates PM10 concentrations are continuing to decrease at similar rates as in the past. The ability for RF models to be interpreted was leveraged using partial dependence plots to explain the observed trends and relevant physical and chemical processes influencing PM10 concentrations. Notably, two regimes were suggested by the models which cause elevated PM10 concentrations in Switzerland: one related to poor dispersion conditions and a second resulting from high rates of secondary PM generation in deep, photochemically active boundary layers. The RF meteorological normalisation process was found to be robust, user friendly and simple to implement, and readily interpretable which suggests the technique could be useful in many air quality exploratory data analysis situations.

Urban Flow and Pollutant Dispersion Simulation with Multi-scale coupling of Meteorological Model with Computational Fluid Dynamic Analysis

NASA Astrophysics Data System (ADS)

Liu, Yushi; Poh, Hee Joo

2014-11-01

The Computational Fluid Dynamics analysis has become increasingly important in modern urban planning in order to create highly livable city. This paper presents a multi-scale modeling methodology which couples Weather Research and Forecasting (WRF) Model with open source CFD simulation tool, OpenFOAM. This coupling enables the simulation of the wind flow and pollutant dispersion in urban built-up area with high resolution mesh. In this methodology meso-scale model WRF provides the boundary condition for the micro-scale CFD model OpenFOAM. The advantage is that the realistic weather condition is taken into account in the CFD simulation and complexity of building layout can be handled with ease by meshing utility of OpenFOAM. The result is validated against the Joint Urban 2003 Tracer Field Tests in Oklahoma City and there is reasonably good agreement between the CFD simulation and field observation. The coupling of WRF- OpenFOAM provide urban planners with reliable environmental modeling tool in actual urban built-up area; and it can be further extended with consideration of future weather conditions for the scenario studies on climate change impact.

Simulating air temperature in an urban street canyon in all weather conditions using measured data at a reference meteorological station

NASA Astrophysics Data System (ADS)

Erell, E.; Williamson, T.

2006-10-01

A model is proposed that adapts data from a standard meteorological station to provide realistic site-specific air temperature in a city street exposed to the same meso-scale environment. In addition to a rudimentary description of the two sites, the canyon air temperature (CAT) model requires only inputs measured at standard weather stations; yet it is capable of accurately predicting the evolution of air temperature in all weather conditions for extended periods. It simulates the effect of urban geometry on radiant exchange; the effect of moisture availability on latent heat flux; energy stored in the ground and in building surfaces; air flow in the street based on wind above roof height; and the sensible heat flux from individual surfaces and from the street canyon as a whole. The CAT model has been tested on field data measured in a monitoring program carried out in Adelaide, Australia, in 2000-2001. After calibrating the model, predicted air temperature correlated well with measured data in all weather conditions over extended periods. The experimental validation provides additional evidence in support of a number of parameterisation schemes incorporated in the model to account for sensible heat and storage flux.

Los Angeles megacity: a high-resolution land–atmosphere modelling system for urban CO 2 emissions

DOE PAGES

Feng, Sha; Lauvaux, Thomas; Newman, Sally; ...

2016-07-22

Megacities are major sources of anthropogenic fossil fuel CO 2 (FFCO 2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km 2 or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO 2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO 2 emission product, Hestia-LA, to simulate atmospheric CO 2 concentrations across the LA megacity at spatial resolutions as fine as ~1 km. We evaluated multiple WRF configurations, selecting one that minimizedmore » errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO 2 emission products to evaluate the impact of the spatial resolution of the CO 2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO 2 concentrations. We find that high spatial resolution in the fossil fuel CO 2 emissions is more important than in the atmospheric model to capture CO 2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO 2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO 2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO 2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO 2 emissions monitoring in the LA megacity requires FFCO 2 emissions modelling with ~1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.« less

Los Angeles megacity: a high-resolution land–atmosphere modelling system for urban CO 2 emissions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Sha; Lauvaux, Thomas; Newman, Sally

Megacities are major sources of anthropogenic fossil fuel CO 2 (FFCO 2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km 2 or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO 2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO 2 emission product, Hestia-LA, to simulate atmospheric CO 2 concentrations across the LA megacity at spatial resolutions as fine as ~1 km. We evaluated multiple WRF configurations, selecting one that minimizedmore » errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO 2 emission products to evaluate the impact of the spatial resolution of the CO 2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO 2 concentrations. We find that high spatial resolution in the fossil fuel CO 2 emissions is more important than in the atmospheric model to capture CO 2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO 2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO 2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO 2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO 2 emissions monitoring in the LA megacity requires FFCO 2 emissions modelling with ~1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.« less

Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe - Part 1: Model description, evaluation of meteorological predictions, and aerosol-meteorology interactions

NASA Astrophysics Data System (ADS)

Zhang, Y.; Sartelet, K.; Wu, S.-Y.; Seigneur, C.

2013-07-01

Comprehensive model evaluation and comparison of two 3-D air quality modeling systems (i.e., the Weather Research and Forecast model (WRF)/Polyphemus and WRF with chemistry and the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) (WRF/Chem-MADRID)) are conducted over Western Europe. Part 1 describes the background information for the model comparison and simulation design, the application of WRF for January and July 2001 over triple-nested domains in Western Europe at three horizontal grid resolutions: 0.5°, 0.125°, and 0.025°, and the effect of aerosol/meteorology interactions on meteorological predictions. Nine simulated meteorological variables (i.e., downward shortwave and longwave radiation fluxes (SWDOWN and LWDOWN), outgoing longwave radiation flux (OLR), temperature at 2 m (T2), specific humidity at 2 m (Q2), relative humidity at 2 m (RH2), wind speed at 10 m (WS10), wind direction at 10 m (WD10), and precipitation (Precip)) are evaluated using available observations in terms of spatial distribution, domainwide daily and site-specific hourly variations, and domainwide performance statistics. The vertical profiles of temperature, dew points, and wind speed/direction are also evaluated using sounding data. WRF demonstrates its capability in capturing diurnal/seasonal variations and spatial gradients and vertical profiles of major meteorological variables. While the domainwide performance of LWDOWN, OLR, T2, Q2, and RH2 at all three grid resolutions is satisfactory overall, large positive or negative biases occur in SWDOWN, WS10, and Precip even at 0.125° or 0.025° in both months and in WD10 in January. In addition, discrepancies between simulations and observations exist in T2, Q2, WS10, and Precip at mountain/high altitude sites and large urban center sites in both months, in particular, during snow events or thunderstorms. These results indicate the model's difficulty in capturing meteorological variables in complex terrain and subgrid-scale meteorological phenomena, due to inaccuracies in model initialization parameterization (e.g., lack of soil temperature and moisture nudging), limitations in the physical parameterizations (e.g., shortwave radiation, cloud microphysics, cumulus parameterizations, and ice nucleation treatments) as well as limitations in surface heat and moisture budget parameterizations (e.g., snow-related processes, subgrid-scale surface roughness elements, and urban canopy/heat island treatments and CO2 domes). While the use of finer grid resolutions of 0.125° and 0.025° shows some improvements for WS10, WD10, Precip, and some mesoscale events (e.g., strong forced convection and heavy precipitation), it does not significantly improve the overall statistical performance for all meteorological variables except for Precip. The WRF/Chem simulations with and without aerosols show that aerosols lead to reduced net shortwave radiation fluxes, 2 m temperature, 10 m wind speed, planetary boundary layer (PBL) height, and precipitation and increase aerosol optical depth, cloud condensation nuclei, cloud optical depth, and cloud droplet number concentrations over most of the domain. These results indicate a need to further improve the model representations of the above parameterizations as well as aerosol-meteorology interactions at all scales.

Can dispersion modeling of air pollution be improved by land-use regression? An example from Stockholm, Sweden

PubMed Central

Korek, Michal; Johansson, Christer; Svensson, Nina; Lind, Tomas; Beelen, Rob; Hoek, Gerard; Pershagen, Göran; Bellander, Tom

2017-01-01

Both dispersion modeling (DM) and land-use regression modeling (LUR) are often used for assessment of long-term air pollution exposure in epidemiological studies, but seldom in combination. We developed a hybrid DM–LUR model using 93 biweekly observations of NOx at 31 sites in greater Stockholm (Sweden). The DM was based on spatially resolved topographic, physiographic and emission data, and hourly meteorological data from a diagnostic wind model. Other data were from land use, meteorology and routine monitoring of NOx. We built a linear regression model for NOx, using a stepwise forward selection of covariates. The resulting model predicted observed NOx (R2=0.89) better than the DM without covariates (R2=0.68, P-interaction <0.001) and with minimal apparent bias. The model included (in descending order of importance) DM, traffic intensity on the nearest street, population (number of inhabitants) within 100 m radius, global radiation (direct sunlight plus diffuse or scattered light) and urban contribution to NOx levels (routine urban NOx, less routine rural NOx). Our results indicate that there is a potential for improving estimates of air pollutant concentrations based on DM, by incorporating further spatial characteristics of the immediate surroundings, possibly accounting for imperfections in the emission data. PMID:27485990

Can dispersion modeling of air pollution be improved by land-use regression? An example from Stockholm, Sweden.

PubMed

Korek, Michal; Johansson, Christer; Svensson, Nina; Lind, Tomas; Beelen, Rob; Hoek, Gerard; Pershagen, Göran; Bellander, Tom

2017-11-01

Both dispersion modeling (DM) and land-use regression modeling (LUR) are often used for assessment of long-term air pollution exposure in epidemiological studies, but seldom in combination. We developed a hybrid DM-LUR model using 93 biweekly observations of NO x at 31 sites in greater Stockholm (Sweden). The DM was based on spatially resolved topographic, physiographic and emission data, and hourly meteorological data from a diagnostic wind model. Other data were from land use, meteorology and routine monitoring of NO x . We built a linear regression model for NO x , using a stepwise forward selection of covariates. The resulting model predicted observed NO x (R 2 =0.89) better than the DM without covariates (R 2 =0.68, P-interaction <0.001) and with minimal apparent bias. The model included (in descending order of importance) DM, traffic intensity on the nearest street, population (number of inhabitants) within 100 m radius, global radiation (direct sunlight plus diffuse or scattered light) and urban contribution to NO x levels (routine urban NO x , less routine rural NO x ). Our results indicate that there is a potential for improving estimates of air pollutant concentrations based on DM, by incorporating further spatial characteristics of the immediate surroundings, possibly accounting for imperfections in the emission data.

Uncertainties in Episodic Ozone Modeling Stemming from Uncertainties in the Meteorological Fields.

NASA Astrophysics Data System (ADS)

Biswas, Jhumoor; Trivikrama Rao, S.

2001-02-01

This paper examines the uncertainty associated with photochemical modeling using the Variable-Grid Urban Airshed Model (UAM-V) with two different prognostic meteorological models. The meteorological fields for ozone episodes that occurred during 17-20 June, 12-15 July, and 30 July-2 August in the summer of 1995 were derived from two meteorological models, the Regional Atmospheric Modeling System (RAMS) and the Fifth-Generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5). The simulated ozone concentrations from the two photochemical modeling systems, namely, RAMS/UAM-V and MM5/UAM-V, are compared with each other and with ozone observations from several monitoring sites in the eastern United States. The overall results indicate that neither modeling system performs significantly better than the other in reproducing the observed ozone concentrations. The results reveal that there is a significant variability, about 20% at the 95% level of confidence, in the modeled 1-h ozone concentration maxima from one modeling system to the other for a given episode. The model-to-model variability in the simulated ozone levels is for most part attributable to the unsystematic type of errors. The directionality for emission controls (i.e., NOx versus VOC sensitivity) is also evaluated with UAM-V using hypothetical emission reductions. The results reveal that not only the improvement in ozone but also the VOC-sensitive and NOx-sensitive regimes are influenced by the differences in the meteorological fields. Both modeling systems indicate that a large portion of the eastern United States is NOx limited, but there are model-to-model and episode-to-episode differences at individual grid cells regarding the efficacy of emission reductions.

Effect Modification of the Association between Short-term Meteorological Factors and Mortality by Urban Heat Islands in Hong Kong

PubMed Central

Goggins, William B.; Chan, Emily Y. Y.; Ng, Edward; Ren, Chao; Chen, Liang

2012-01-01

Background Prior studies from around the world have indicated that very high temperatures tend to increase summertime mortality. However possible effect modification by urban micro heat islands has only been examined by a few studies in North America and Europe. This study examined whether daily mortality in micro heat island areas of Hong Kong was more sensitive to short term changes in meteorological conditions than in other areas. Method An urban heat island index (UHII) was calculated for each of Hong Kong’s 248 geographical tertiary planning units (TPU). Daily counts of all natural deaths among Hong Kong residents were stratified according to whether the place of residence of the decedent was in a TPU with high (above the median) or low UHII. Poisson Generalized Additive Models (GAMs) were used to estimate the association between meteorological variables and mortality while adjusting for trend, seasonality, pollutants and flu epidemics. Analyses were restricted to the hot season (June-September). Results Mean temperatures (lags 0–4) above 29°C and low mean wind speeds (lags 0–4) were significantly associated with higher daily mortality and these associations were stronger in areas with high UHII. A 1°C rise above 29°C was associated with a 4.1% (95% confidence interval (CI): 0.7%, 7.6%) increase in natural mortality in areas with high UHII but only a 0.7% (95% CI: −2.4%, 3.9%) increase in low UHII areas. Lower mean wind speeds (5th percentile vs. 95th percentile) were associated with a 5.7% (95% CI: 2.7, 8.9) mortality increase in high UHII areas vs. a −0.3% (95% CI: −3.2%, 2.6%) change in low UHII areas. Conclusion The results suggest that urban micro heat islands exacerbate the negative health consequences of high temperatures and low wind speeds. Urban planning measures designed to mitigate heat island effects may lessen the health effects of unfavorable summertime meteorological conditions. PMID:22761684

Communicating Climate Hazards Information in the Urban Community to the Public

NASA Astrophysics Data System (ADS)

McCalla, M. R.

2004-12-01

Climate simulations are predicting an overall warming of the atmosphere due to greenhouse gases. For example, CO2 allows sunlight to reach the earth and warm its surface, but it prevents a portion of this surface heat from escaping the atmosphere. This greenhouse effect can result in higher mean atmospheric temperatures near the Earth's surface. If these predictions are correct, changes in temperature can increase the power demand to cool urban building structures (homes, schools, offices, storage facilities, etc.). Similarly, the regional and seasonal temperature fluctuations due to climate oscillations (El Nino, for example) may also increase the power demand for heating and cooling. A warming climate (or cooling climate, for that matter) can also affect the available water for drinking, irrigation, and generating power, all of which impact the viability and sustainability of the urban community. Additionally, urban areas are expanding. Consequently, the distance between city and wildlands is decreasing. The wildland-urban interface often stresses biodiversity, forestation, and the urban area's ability to respond adequately to such climate-induced hazards as forest fires, flooding, and coastal erosion. Thus climate has an impact on humans and vice versa. How can scientists communicate the impact of climate on the urban community? What is the best way to communicate the information so that the public can (1) be informed and (2) make informed decisions? How well is the nexus between climate science and impacts on and benefits to decision makers understood? What is the best way to fully exploit that connection so that the public can develop intervention measures to support the urban community's response to climatic impacts? The Office of the Federal Coordinator for Meteorological Services and Supporting Research (OFCM) is an interdepartmental office established in response to Public Law 87-843 with the express purpose of ensuring the effective use of federal meteorological resources by leading the systematic coordination of operational weather and climate requirements, services, products, capabilities, information, modeling, and supporting research among the federal agencies. Toward that end, the OFCM, in partnership with the Department of Homeland Security Science and Technology Directorate, is sponsoring a September 2004 forum on urban meteorology. The theme of the forum is "Information to Improve Community Responses to Urban Atmospheric Hazards, Weather Events, and Climate." Forum participants and speakers will come from both the public and private sectors, as well as the academic community. The output of the forum will be to specifically answer such questions as (1) how will emerging technologies help communicate risks more effectively to the urban community; (2) how can education, outreach, and training be more effective in eliciting an appropriate public response; and (3) what methods are needed to better communicate and disseminate climate information to the public? The communication recommendations stemming from the urban meteorology forum will be shared with AGU conference participants.

Urban impact on air quality in RegCM/CAMx couple for MEGAPOLI project - high resolution sensitivity study

NASA Astrophysics Data System (ADS)

Halenka, T.; Huszar, P.; Belda, M.

2010-09-01

Recent studies show considerable effect of atmospheric chemistry and aerosols on climate on regional and local scale. For the purpose of qualifying and quantifying the magnitude of climate forcing due to atmospheric chemistry/aerosols on regional scale, the development of coupling of regional climate model and chemistry/aerosol model was started on the Department of Meteorology and Environmental Protection, Charles University, Prague, for the EC FP6 Project QUANTIFY and EC FP6 Project CECILIA. For this coupling, existing regional climate model and chemistry transport model have been used at very high resolution of 10km grid. Climate is calculated using RegCM while chemistry is solved by CAMx. The experiments with the couple have been prepared for EC FP7 project MEGAPOLI assessing the impact of the megacities and industrialized areas on climate. Meteorological fields generated by RCM drive CAMx transport, chemistry and a dry/wet deposition. A preprocessor utility was developed for transforming RegCM provided fields to CAMx input fields and format. New domain have been settled for MEGAPOLI purpose in 10km resolution including all the European "megacities" regions, i.e. London metropolitan area, Paris region, industrialized Ruhr area, Po valley etc. There is critical issue of the emission inventories available for 10km resolution including the urban hot-spots, TNO emissions are adopted for this sensitivity study in 10km resolution for comparison of the results with the simulation based on merged TNO emissions, i.e. basically original EMEP emissions at 50 km grid. The sensitivity test to switch on/off Paris area emissions is analysed as well. Preliminary results for year 2005 are presented and discussed to reveal whether the concept of effective emission indices could help to parameterize the urban plume effects in lower resolution models. Interactive coupling is compared to study the potential of possible impact of urban air-pollution to the urban area climate.

Determination of the optimal training principle and input variables in artificial neural network model for the biweekly chlorophyll-a prediction: a case study of the Yuqiao Reservoir, China.

PubMed

Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang

2015-01-01

Predicting the levels of chlorophyll-a (Chl-a) is a vital component of water quality management, which ensures that urban drinking water is safe from harmful algal blooms. This study developed a model to predict Chl-a levels in the Yuqiao Reservoir (Tianjin, China) biweekly using water quality and meteorological data from 1999-2012. First, six artificial neural networks (ANNs) and two non-ANN methods (principal component analysis and the support vector regression model) were compared to determine the appropriate training principle. Subsequently, three predictors with different input variables were developed to examine the feasibility of incorporating meteorological factors into Chl-a prediction, which usually only uses water quality data. Finally, a sensitivity analysis was performed to examine how the Chl-a predictor reacts to changes in input variables. The results were as follows: first, ANN is a powerful predictive alternative to the traditional modeling techniques used for Chl-a prediction. The back program (BP) model yields slightly better results than all other ANNs, with the normalized mean square error (NMSE), the correlation coefficient (Corr), and the Nash-Sutcliffe coefficient of efficiency (NSE) at 0.003 mg/l, 0.880 and 0.754, respectively, in the testing period. Second, the incorporation of meteorological data greatly improved Chl-a prediction compared to models solely using water quality factors or meteorological data; the correlation coefficient increased from 0.574-0.686 to 0.880 when meteorological data were included. Finally, the Chl-a predictor is more sensitive to air pressure and pH compared to other water quality and meteorological variables.

Effects of Land-use/Land-cover and Climate Changes on Water Quantity and Quality in Sub-basins near Major US Cities in the Great Lakes Region

NASA Astrophysics Data System (ADS)

Murphy, L.; Al-Hamdan, M. Z.; Crosson, W. L.; Barik, M.

2017-12-01

Land-cover change over time to urbanized, less permeable surfaces, leads to reduced water infiltration at the location of water input while simultaneously transporting sediments, nutrients and contaminants farther downstream. With an abundance of agricultural fields bordering the greater urban areas of Milwaukee, Detroit, and Chicago, water and nutrient transport is vital to the farming industry, wetlands, and communities that rely on water availability. Two USGS stream gages each located within a sub-basin near each of these Great Lakes Region cities were examined, one with primarily urban land-cover between 1992 and 2011, and one with primarily agriculture land-cover. ArcSWAT, a watershed model and soil and water assessment tool used in extension with ArcGIS, was used to develop hydrologic models that vary the land-covers to simulate surface runoff during a model run period from 2004 to 2008. Model inputs that include a digital elevation model (DEM), Landsat-derived land-use/land-cover (LULC) satellite images from 1992, 2001, and 2011, soil classification, and meteorological data were used to determine the effect of different land-covers on the water runoff, nutrients and sediments. The models were then calibrated and validated to USGS stream gage data measurements over time. Additionally, the watershed model was run based on meteorological data from an IPCC CMIP5 high emissions climate change scenario for 2050. Model outputs from the different LCLU scenarios were statistically evaluated and results showed that water runoff, nutrients and sediments were impacted by LULC change in four out of the six sub-basins. In the 2050 climate scenario, only one out of the six sub-basin's water quantity and quality was affected. These results contribute to the importance of developing hydrologic models as the dependence on the Great Lakes as a freshwater resource competes with the expansion of urbanization leading to the movement of runoff, nutrients, and sediments off the land.

Model study of meteorology and photochemical air pollution over un urban area in south-eastern France (ESCOMPTE campaign).

NASA Astrophysics Data System (ADS)

Taghavi, M.; Cautenet, S.

2003-04-01

The ESCOMPTE Campaign has been conducted over Southern France (Provence region including the Marseille, Aix and Toulon cities and the Fos-Berre industrial center) in June and July of 2001. In order to study the redistribution of the pollutants emitted by anthropic and biogenic emissions and their impact on the atmospheric chemistry, we used meso-scale modeling (RAMS model, paralleled version 4.3, coupled on line with chemical modules : MOCA2.2 (Poulet et al, 2002) including 29 gaseous species). The hourly high resolution emissions were obtained from ESCOMPTE database (Ponche et al, 2002). The model was coupled with the dry deposition scheme (Walmsley and Weseley,1996). In this particular case of complex circulation (sea breeze associated with topography), the processes involving peaks of pollution were strongly non linear, and the meso scale modeling coupled on line with chemistry module was an essential step for a realistic redistribution of chemical species. Two nested grids satisfactorily describe the synoptic dynamics and the sea breeze circulations. The ECMWF meteorological fields provide the initial and boundary conditions. Different events characterized by various meteorological situations were simulated. Meteorological fields retrieved by modeling, also Modeled ozone, NOx, CO and SO2 concentrations, were compared with balloons, lidars, aircrafts and surface stations measurements. The chemistry regimes were explained according to the distribution of plumes. The stratified layers were examined.

Numerical simulation of the impact of reforestation on winter meteorology and environment in a semi-arid urban valley, Northwestern China.

PubMed

Yu, Ye; He, Jianjun; Zhao, Suping; Liu, Na; Chen, Jinbei; Mao, Hongjun; Wu, Lin

2016-11-01

Since 1999 Chinese government has made great effort to reforest the south and north mountains surrounding urban Lanzhou - a city located in a river valley, Northwestern China. Until 2009 obvious land use change occurred, with 69.2% of the reforested area been changed from grasslands, croplands, barren or sparsely vegetated land to closed shrublands and 20.6% from closed shrublands, grasslands, and croplands to forests. Reforestation changes land-surface properties, with possible impact on the evolution of atmospheric variables. To understand to what extent the local meteorology and environment could be affected by reforestation in winter, and through what processes, two sets of simulations were conducted using the Weather Research and Forecasting model (WRF) and the FLEXible PARTicle (FLEXPART) dispersion model for a control case with high-resolution remotely sensed land cover data for 2009 and a scenario assuming no reforestation since 1999. Results suggested that the changes in albedo, surface exchange coefficient and surface soil heat conductivity related to reforestation led to the changes in surface net radiation and surface energy partitioning, which in turn affected the meteorological fields and enhanced the mountain-valley wind circulation. Replacement of shrublands and grassland with forest in the south mountain through reforestation play a dominant role in the enhancement of mountain-valley wind circulation. Reforestation increased the amount of air exchanged between the valley and the outside during the day, with the largest hourly increase of 10% on calm weather days and a monthly mean hourly increase of 2% for the study period (Dec. 2009). Reforestation affected the spatial distribution of pollutants and slightly improved the urban air quality, especially in the eastern valley. Results from this study provide useful information for future urban air quality management and reforestation plan, and some experience for cities with similar situations in the world. Copyright © 2016 Elsevier B.V. All rights reserved.

Meteorological and urban landscape factors on severe air pollution in Beijing.

PubMed

Han, Lijian; Zhou, Weiqi; Li, Weifeng; Meshesha, Derege T; Li, Li; Zheng, Mingqing

2015-07-01

Air pollution gained special attention with the rapid development in Beijing. In January 2013, Beijing experienced extreme air pollution, which was not well examined. We thus examine the magnitude of air quality in the particular month by applying the air quality index (AQI), which is based on the newly upgraded Chinese environmental standard. Our finding revealed that (1) air quality has distinct spatial heterogeneity and relatively better air quality was observed in the northwest while worse quality happened in the southeast part of the city; (2) the wind speed is the main determinant of air quality in the city-when wind speed is greater than 4 m/sec, air quality can be significantly improved; and (3) urban impervious surface makes a contribution to the severity of air pollution-that is, with an increase in the fraction of impervious surface in a given area, air pollution is more severe. The results from our study demonstrated the severe pollution in Beijing and its meteorological and landscape factors. Also, the results of this work suggest that very strict air quality management should be conducted when wind speed less than 4 m/sec, especially at places with a large fraction of urban impervious surface. Prevention of air pollution is rare among methods with controls on meteorological and urban landscape conditions. We present research that utilizes the latest air quality index (AQI) to compare air pollution with meteorological and landscape conditions. We found that wind is the major meteorological factor that determines the air quality. For a given wind speed greater than 4 m/sec, the air quality improved significantly. Urban impervious surface also contributes to the severe air pollution: that is, when the fraction of impervious surface increases, there is more severe air pollution. These results suggest that air quality management should be conducted when wind speed is less than 4 m/sec, especially at places with a larger fraction of urban impervious surface.

Impact of WRF model PBL schemes on air quality simulations over Catalonia, Spain.

PubMed

Banks, R F; Baldasano, J M

2016-12-01

Here we analyze the impact of four planetary boundary-layer (PBL) parametrization schemes from the Weather Research and Forecasting (WRF) numerical weather prediction model on simulations of meteorological variables and predicted pollutant concentrations from an air quality forecast system (AQFS). The current setup of the Spanish operational AQFS, CALIOPE, is composed of the WRF-ARW V3.5.1 meteorological model tied to the Yonsei University (YSU) PBL scheme, HERMES v2 emissions model, CMAQ V5.0.2 chemical transport model, and dust outputs from BSC-DREAM8bv2. We test the performance of the YSU scheme against the Assymetric Convective Model Version 2 (ACM2), Mellor-Yamada-Janjic (MYJ), and Bougeault-Lacarrère (BouLac) schemes. The one-day diagnostic case study is selected to represent the most frequent synoptic condition in the northeast Iberian Peninsula during spring 2015; regional recirculations. It is shown that the ACM2 PBL scheme performs well with daytime PBL height, as validated against estimates retrieved using a micro-pulse lidar system (mean bias=-0.11km). In turn, the BouLac scheme showed WRF-simulated air and dew point temperature closer to METAR surface meteorological observations. Results are more ambiguous when simulated pollutant concentrations from CMAQ are validated against network urban, suburban, and rural background stations. The ACM2 scheme showed the lowest mean bias (-0.96μgm -3 ) with respect to surface ozone at urban stations, while the YSU scheme performed best with simulated nitrogen dioxide (-6.48μgm -3 ). The poorest results were with simulated particulate matter, with similar results found with all schemes tested. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Influence of land use and meteorological factors on the spatial distribution of Toxocara canis and Toxocara cati eggs in soil in urban areas.

PubMed

Gao, Xiang; Wang, Hongbin; Li, Jianxin; Qin, Hongyu; Xiao, Jianhua

2017-01-15

Soil which has been contaminated by Toxocara spp. eggs is considered as one of the main infection sources of Toxocariasis in animals and humans. The present study conducted a detailed investigation into the spatial patterns of Toxocara canis (T. canis) and Toxocara cati (T. cati) eggs in soil in urban area of northeastern Mainland China, and assessed the inter-relationships between meteorological factors, land use and the distribution of the Toxocara spp. eggs. Polymerase chain reaction (PCR) was used for the determination of T. canis and T. cati eggs contamination in soil samples. Between April 2014 and May 2015, 9420 soil samples were subjected to PCR examination and 7027 sheep (74.6%) were determined to be positive for T. canis and T. cati eggs. Subsequently, we evaluated the effect of land use, and meteorological factors on the spatial distribution of T. canis and T. cati eggs based on a maximum entropy model. Jackknife analysis revealed that the area of residential land, wood and grass land and precipitation may influence the occurrence of T. canis and T. cati eggs in soil. Our findings indicate that land use and meteorological factors may be important variables affecting transmission of Toxocariasis and should be taken into account in the development of future surveillance programmes for Toxocariasis. Copyright © 2016 Elsevier B.V. All rights reserved.

Modeling the energy balance in Marseille: Sensitivity to roughness length parameterizations and thermal admittance

NASA Astrophysics Data System (ADS)

Demuzere, M.; De Ridder, K.; van Lipzig, N. P. M.

2008-08-01

During the ESCOMPTE campaign (Experience sur Site pour COntraindre les Modeles de Pollution atmospherique et de Transport d'Emissions), a 4-day intensive observation period was selected to evaluate the Advanced Regional Prediction System (ARPS), a nonhydrostatic meteorological mesoscale model that was optimized with a parameterization for thermal roughness length to better represent urban surfaces. The evaluation shows that the ARPS model is able to correctly reproduce temperature, wind speed, and direction for one urban and two rural measurements stations. Furthermore, simulated heat fluxes show good agreement compared to the observations, although simulated sensible heat fluxes were initially too low for the urban stations. In order to improve the latter, different roughness length parameterization schemes were tested, combined with various thermal admittance values. This sensitivity study showed that the Zilitinkevich scheme combined with and intermediate value of thermal admittance performs best.

Meteorological effects on the levels of fecal indicator bacteria in an urban stream: a modeling approach.

PubMed

Cho, Kyung Hwa; Cha, Sung Min; Kang, Joo-Hyon; Lee, Seung Won; Park, Yongeun; Kim, Jung-Woo; Kim, Joon Ha

2010-04-01

Gwangju Creek (GJC) in Korea, which drains a highly urbanized watershed, has suffered from substantial fecal contamination, thereby limiting the beneficial use of the water in addition to threatening public health. In this study, to quantitatively estimate the sinks and sources of fecal indicator bacteria (FIB) in GJC under varying meteorological conditions, two FIB (i.e., Escherichia coli and enterococci bacteria) were monitored hourly for 24h periods during both wet and dry weather conditions at four sites along GJC, and the collected data was subsequently used to develop a spatiotemporal FIB prediction model. The monitoring data revealed that storm washoff and irradiational die-off by sunlight are the two key processes controlling FIB populations in wet and dry weather, respectively. FIB populations significantly increased during precipitation, with greater concentrations occurring at higher rainfall intensity. During dry weather, FIB populations decreased in the presence of sunlight in daytime but quickly recovered at nighttime due to continuous point-source inputs. In this way, the contributions of the key processes (i.e., irradiational die-off by sunlight, settling, storm washoff, and resuspension) to the FIB levels in GJC under different meteorological conditions were quantitatively estimated using the developed model. The modeling results showed that the die-off by sunlight is the major sink of FIB during the daytime in dry weather with a minor contribution from the settling process. During wet weather, storm washoff and resuspension are equally important processes that are responsible for the substantial increase of FIB populations. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

Assessing the impact of local meteorological variables on surface ozone in Hong Kong during 2000-2015 using quantile and multiple line regression models

NASA Astrophysics Data System (ADS)

Zhao, Wei; Fan, Shaojia; Guo, Hai; Gao, Bo; Sun, Jiaren; Chen, Laiguo

2016-11-01

The quantile regression (QR) method has been increasingly introduced to atmospheric environmental studies to explore the non-linear relationship between local meteorological conditions and ozone mixing ratios. In this study, we applied QR for the first time, together with multiple linear regression (MLR), to analyze the dominant meteorological parameters influencing the mean, 10th percentile, 90th percentile and 99th percentile of maximum daily 8-h average (MDA8) ozone concentrations in 2000-2015 in Hong Kong. The dominance analysis (DA) was used to assess the relative importance of meteorological variables in the regression models. Results showed that the MLR models worked better at suburban and rural sites than at urban sites, and worked better in winter than in summer. QR models performed better in summer for 99th and 90th percentiles and performed better in autumn and winter for 10th percentile. And QR models also performed better in suburban and rural areas for 10th percentile. The top 3 dominant variables associated with MDA8 ozone concentrations, changing with seasons and regions, were frequently associated with the six meteorological parameters: boundary layer height, humidity, wind direction, surface solar radiation, total cloud cover and sea level pressure. Temperature rarely became a significant variable in any season, which could partly explain the peak of monthly average ozone concentrations in October in Hong Kong. And we found the effect of solar radiation would be enhanced during extremely ozone pollution episodes (i.e., the 99th percentile). Finally, meteorological effects on MDA8 ozone had no significant changes before and after the 2010 Asian Games.

Controlling Factors of the Surface Energy and Water Balances in cities located in cold climate regions

NASA Astrophysics Data System (ADS)

Järvi, L.; Grimmond, S. B.; Christen, A.; McFadden, J. P.; Strachan, I. B.

2016-12-01

Urban effects on climate are often pronounced in winter due to large anthropogenic heat releases and differences in snow cover between urban and surrounding rural areas. In this study, we simulate energy and water balances in cities characterized by cold winter climates with snow. Eleven urban sites from Helsinki (Finland), Basel (Switzerland), Montreal (Canada) and Minneapolis (USA) are analysed. The sites were selected based on the availability of either measured turbulent fluxes (from eddy covariance) or surface runoff to be used for model evaluation. The sites vary with respect to land cover fractions, irrigation habits and population densities. For example, the plan area fraction of impervious surface varies from 5% in Minneapolis to 84% in Basel. To simulate urban energy and water balances, we use the Surface Urban Energy and Water balance Scheme (SUEWS) model, which has been designed to minimize the number of required input variables and model parameters. For each site, the model is run in an offline mode using measured hourly meteorological data with a time step of 5-min. As the modelled time periods range from one (Basel) to 7.5 years (Helsinki), a wide range of meteorological conditions occur. Our results show how both evaporation and surface runoff are highly dependent on the fraction of impervious surface cover (r > |0.8|) during snow-free periods. However, high year-to-year variability in simulated evaporation and runoff indicates that climatological factors are also important. In winter, the amount and duration of snow cover become import controlling factor in determining the two components of water balance. The shorter the snow cover period is, the larger the cumulative runoff tends to be. Thus, our results suggest that warmer winters with less snow will increase the stress on drainage systems and modify the urban ecosystem via changes in evaporation and Bowen ratio. Also, our results indicate that simply using the fraction of impervious or pervious surfaces when estimating the surface runoff at different sites is not sufficient, but rather inter-annual variability in climatology also needs to be considered.

Decadal evaluation of regional climate, air quality, and their interactions using WRF/Chem Version 3.6.1

NASA Astrophysics Data System (ADS)

Yahya, K.; Wang, K.; Campbell, P.; Glotfelty, T.; He, J.; Zhang, Y.

2015-08-01

The Weather Research and Forecasting model with Chemistry (WRF/Chem) v3.6.1 with the Carbon Bond 2005 (CB05) gas-phase mechanism is evaluated for its first decadal application during 2001-2010 using the Representative Concentration Pathway (RCP 8.5) emissions to assess its capability and appropriateness for long-term climatological simulations. The initial and boundary conditions are downscaled from the modified Community Earth System Model/Community Atmosphere Model (CESM/CAM5) v1.2.2. The meteorological initial and boundary conditions are bias-corrected using the National Center for Environmental Protection's Final (FNL) Operational Global Analysis data. Climatological evaluations are carried out for meteorological, chemical, and aerosol-cloud-radiation variables against data from surface networks and satellite retrievals. The model performs very well for the 2 m temperature (T2) for the 10 year period with only a small cold bias of -0.3 °C. Biases in other meteorological variables including relative humidity at 2 m, wind speed at 10 m, and precipitation tend to be site- and season-specific; however, with the exception of T2, consistent annual biases exist for most of the years from 2001 to 2010. Ozone mixing ratios are slightly overpredicted at both urban and rural locations but underpredicted at rural locations. PM2.5 concentrations are slightly overpredicted at rural sites, but slightly underpredicted at urban/suburban sites. In general, the model performs relatively well for chemical and meteorological variables, and not as well for aerosol-cloud-radiation variables. Cloud-aerosol variables including aerosol optical depth, cloud water path, cloud optical thickness, and cloud droplet number concentration are generally underpredicted on average across the continental US. Overpredictions of several cloud variables over eastern US result in underpredictions of radiation variables and overpredictions of shortwave and longwave cloud forcing which are important climate variables. While the current performance is deemed to be acceptable, improvements to the bias-correction method for CESM downscaling and the model parameterizations of cloud dynamics and thermodynamics, as well as aerosol-cloud interactions can potentially improve model performance for long-term climate simulations.

Intercomparison of the community multiscale air quality model and CALGRID using process analysis.

PubMed

O'Neill, Susan M; Lamb, Brian K

2005-08-01

This study was designed to examine the similarities and differences between two advanced photochemical air quality modeling systems: EPA Models-3/CMAQ and CALGRID/CALMET. Both modeling systems were applied to an ozone episode that occurred along the I-5 urban corridor in western Washington and Oregon during July 11-14, 1996. Both models employed the same modeling domain and used the same detailed gridded emission inventory. The CMAQ model was run using both the CB-IV and RADM2 chemical mechanisms, while CALGRID was used with the SAPRC-97 chemical mechanism. Outputfrom the Mesoscale Meteorological Model (MM5) employed with observational nudging was used in both models. The two modeling systems, representing three chemical mechanisms and two sets of meteorological inputs, were evaluated in terms of statistical performance measures for both 1- and 8-h average observed ozone concentrations. The results showed that the different versions of the systems were more similar than different, and all versions performed well in the Portland region and downwind of Seattle but performed poorly in the more rural region north of Seattle. Improving the meteorological input into the CALGRID/CALMET system with planetary boundary layer (PBL) parameters from the Models-3/CMAQ meteorology preprocessor (MCIP) improved the performance of the CALGRID/CALMET system. The 8-h ensemble case was often the best performer of all the cases indicating that the models perform better over longer analysis periods. The 1-h ensemble case, derived from all runs, was not necessarily an improvement over the five individual cases, but the standard deviation about the mean provided a measure of overall modeling uncertainty. Process analysis was applied to examine the contribution of the individual processes to the species conservation equation. The process analysis results indicated that the two modeling systems arrive at similar solutions by very different means. Transport rates are faster and exhibit greater fluctuations in the CMAQ cases than in the CALGRID cases, which lead to different placement of the urban ozone plumes. The CALGRID cases, which rely on the SAPRC97 chemical mechanism, exhibited a greater diurnal production/loss cycle of ozone concentrations per hour compared to either the RADM2 or CBIV chemical mechanisms in the CMAQ cases. These results demonstrate the need for specialized process field measurements to confirm whether we are modeling ozone with valid processes.

Crowdsourcing urban air temperatures from smartphone battery temperatures

NASA Astrophysics Data System (ADS)

Overeem, A.; Robinson, J. C. R.; Leijnse, H.; Steeneveld, G. J.; Horn, B. K. P.; Uijlenhoet, R.

2013-08-01

Accurate air temperature observations in urban areas are important for meteorology and energy demand planning. They are indispensable to study the urban heat island effect and the adverse effects of high temperatures on human health. However, the availability of temperature observations in cities is often limited. Here we show that relatively accurate air temperature information for the urban canopy layer can be obtained from an alternative, nowadays omnipresent source: smartphones. In this study, battery temperatures were collected by an Android application for smartphones. A straightforward heat transfer model is employed to estimate daily mean air temperatures from smartphone battery temperatures for eight major cities around the world. The results demonstrate the enormous potential of this crowdsourcing application for real-time temperature monitoring in densely populated areas.

Meteorologic and Geographic Barriers to Physical Activity in a Workplace Wellness Program.

PubMed

Smith, Karen C; Michl, Griffin L; Katz, Jeffrey N; Losina, Elena

2018-02-01

Inclement weather and home environment can act as barriers to physical activity. However, it is unclear if they reduce the activity of persons participating in activity-promoting programs. Data from a 6-month workplace financial incentives program were used to establish the association between meteorologic (temperature, rain, snow, and wind) and geographic factors (urban/nonurban home location and distance between home and work) and moderate to vigorous physical activity (MVPA). Multivariable models were built to estimate mean weekly minutes of MVPA adjusting for demographic factors, clinical factors, and impulsivity. The 292 participants had a mean age of 38 (SD = 11) years. Eighty-three percent were female and 62% were white. Twenty-nine percent lived within 3 miles of work, and 35% lived in urban areas. Participants who lived more than 3 miles from work averaged 75 [95% confidence interval (CI), 65-84] minutes of weekly MVPA compared with 105 (95% CI, 88-122) minutes for those who lived within 3 miles of work. Urban participants averaged 70 (95% CI, 57-83) minutes of MVPA compared with 91 (95% CI, 80-102) minutes for nonurban participants. Colder temperatures were associated with decreased MVPA, and impulsivity modified the effect. Colder temperatures, greater distance from work, and an urban residence are associated with fewer minutes of MVPA.

Modeling Urban Air Quality in the Berlin-Brandenburg Region: Evaluation of a WRF-Chem Setup

NASA Astrophysics Data System (ADS)

Kuik, F.; Churkina, G.; Butler, T. M.; Lauer, A.; Mar, K. A.

2015-12-01

Air pollution is the number one environmental cause of premature deaths in Europe. Despite extensive regulations, air pollution remains a challenging issue, especially in urban areas. For studying air quality in the Berlin-Brandenburg region of Germany the Weather Research and Forecasting Model with Chemistry (WRF-Chem) is set up and evaluated against meteorological and air quality observations from monitoring stations as well as from a field campaign conducted in 2014 (incl. black carbon, VOCs as well as mobile measurements of particle size distribution and particle mass). The model setup includes 3 nested domains with horizontal resolutions of 15km, 3km, and 1km, online biogenic emissions using MEGAN 2.0, and anthropogenic emissions from the TNO-MACC-II inventory. This work serves as a basis for future studies on different aspects of air pollution in the Berlin-Brandenburg region, including how heat waves affect emissions of biogenic volatile organic compounds (BVOC) from urban vegetation (summer 2006) and the impact of selected traffic measures on air quality in the Berlin-Brandenburg area (summer 2014). The model represents the meteorology as observed in the region well for both periods. An exception is the heat wave period in 2006, where the temperature simulated with 3km and 1km resolutions is biased low by around 2°C for urban built-up stations. First results of simulations with chemistry show that, on average, WRF-Chem simulates concentrations of O3 well. However, the 8 hr maxima are underestimated, and the minima are overestimated. While NOx daily means are modeled reasonably well for urban stations, they are overestimated for suburban stations. PM10 concentrations are underestimated by the model. The biases and correlation coefficients of simulated O3, NOx, and PM10 in comparison to surface observations do not show improvements for the 1km domain in comparison to the 3km domain. To improve the model performance of the 1km domain we will include an updated emission inventory (TNO-MACC-III) as well as the interpolation of the emission data from 7km to a 1km resolution.

Simulations of Moscow megacity heat island with the COSMO-CLM model using two different urban canopy schemes and realistic building parameters, derived from OpenStreetMap data

NASA Astrophysics Data System (ADS)

Varentsov, Mikhail; Wouters, Hendrik; Trusilova, Kristina; Samsonov, Timofey; Konstantinov, Pavel

2017-04-01

In this study we present the application of the regional climate model COSMO-CLM to simulate urban heat island (UHI) phenomenon for Moscow megacity, which is the biggest agglomeration in Europe (with modern population of more than 17 million people). Significant differences of Moscow from the cities of Western Europe are related with much more continental climate with higher diurnal and annual temperature variations, and with specific building features such as its high density and almost total predominance of high-rise and low-rise blocks of flats on the private low-rise houses. Because of these building and climate features, the UHI of Moscow megacity is stronger than UHIs of many other cities of the similar size, with a mean intensity is about 2 °C and maximum intensity reaching up to 13 °C (Lokoschenko, 2014). Such a pronounced UHI together with the existence of an extensive observation network (more than 50 weather and air quality monitoring stations and few microwave temperature profilers) within the city and its surrounding make Moscow an especially interesting place for urban climate researches and good testbed for urban canopy models. In our numerical experiments, regional climate model firstly was adapted for investigated region with aim to improve quality of its simulations of rural areas. Then, to take into account urban canopy effects on thermal regime of the urbanized areas, we used two different versions of COSMO-CLM model. First is coupled with TEB (Town Energy Balance) single layer urban canopy model (Trusilova, 2013), and second is extended with bulk urban canopy scheme TERRA_URB using the Semi-empircal URban-canopY dependency parametriation SURY (Wouters et. al, 2016). Numerical experiments with these two versions of the model were run with spatial resolution about 1 km for several summer and winter months. To provide specific parameters, required for urban parameterizations, such as urban fraction, building height and street canyon aspect ratio, we used originally technology of GIS-based processing of realistic OpenStreetMap data, which includes size and shape of the most of the in the city (Samsonov et al., 2015). Our testbed allows to make more detailed comparison between the modelling approaches, and also reveals the importance of correct definition of the of turbulent mixing in the ABL in the atmospheric model, and the realistic specification of the building morphology parameters and anthropogenic heat fluxes. In addition, strong seasonal variation of the importance of different factors, responsible for UHI appearance, was shown. Moreover, the framework allows to identify and solve issues regarding the different model approaches: detailed analysis of spatial and temporal variations of modelled urban temperature anomalies and their vertical extent has shown that version of COSMO-CLM model with TERRA-URB scheme simulate UHI effect in more realistic way. Research was supported by Russian Foundation for Basic Research (RFBR) and Russian Geographic Society (RGS): RFBR projects № 16-35-00474, 15-35-21129 and 16-05-00704 A, RGS-RFBR project № 13-05-41306. References: 1. Lokoshchenko, M. A. (2014). Urban 'heat island' in Moscow. Urban Climate, 10, 550-562. 2. Samsonov, T. E., Konstantinov, P. I., & Varentsov, M. I. (2015). Object-oriented approach to urban canyon analysis and its applications in meteorological modeling. Urban Climate, 13, 122-139. 3. Trusilova K., Früh, B., Brienen, S., Walter, A., Masson, V., Pigeon, G., Becker, P. Implementation of an Urban Parameterization Scheme into the Regional Climate Model COSMO-CLM// Journal of Applied Meteorology and Climatology. 2013. Vol. 52. P. 2296-2311. 4. Wouters, H., Demuzere, M., Blahak, U., Fortuniak, K., Maiheu, B., Camps, J., & van Lipzig, N. P. (2016). The efficient urban canopy dependency parametrization (SURY) v1.0 for atmospheric modelling: description and application with the COSMO-CLM model for a Belgian summer. Geoscientific Model Development, 9(9), 3027-3054.

The role of a peri-urban forest on air quality improvement in the Mexico City megalopolis.

PubMed

Baumgardner, Darrel; Varela, Sebastian; Escobedo, Francisco J; Chacalo, Alicia; Ochoa, Carlos

2012-04-01

Air quality improvement by a forested, peri-urban national park was quantified by combining the Urban Forest Effects (UFORE) and the Weather Research and Forecasting coupled with Chemistry (WRF-Chem) models. We estimated the ecosystem-level annual pollution removal function of the park's trees, shrub and grasses using pollution concentration data for carbon monoxide (CO), ozone (O(3)), and particulate matter less than 10 microns in diameter (PM(10)), modeled meteorological and pollution variables, and measured forest structure data. Ecosystem-level O(3) and CO removal and formation were also analyzed for a representative month. Total annual air quality improvement of the park's vegetation was approximately 0.02% for CO, 1% for O(3,) and 2% for PM(10), of the annual concentrations for these three pollutants. Results can be used to understand the air quality regulation ecosystem services of peri-urban forests and regional dynamics of air pollution emissions from major urban areas. Copyright © 2011 Elsevier Ltd. All rights reserved.

Spatial Growth Modeling and High Resolution Remote Sensing Data Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Johnson, Hoyt; Khan, Maudood

2006-01-01

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world s population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include business as usual and smart growth scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS lkm land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Remote Sensing and Spatial Growth Modeling Coupled With Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

NASA Astrophysics Data System (ADS)

Quattrochi, D. A.; Estes, M. G.; Crosson, W. L.; Johnson, H.; Khan, M.

2006-05-01

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world's population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS 1km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta's growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Modelling the variation of land surface temperature as determinant of risk of heat-related health events

PubMed Central

2011-01-01

Background The evaluation of exposure to ambient temperatures in epidemiological studies has generally been based on records from meteorological stations which may not adequately represent local temperature variability. Here we propose a spatially explicit model to estimate local exposure to temperatures of large populations under various meteorological conditions based on satellite and meteorological data. Methods A general linear model was used to estimate surface temperatures using 15 LANDSAT 5 and LANDSAT 7 images for Quebec Province, Canada between 1987 and 2002 and spanning the months of June to August. The images encompassed both rural and urban landscapes and predictors included: meteorological records of temperature and wind speed, distance to major water bodies, Normalized Differential Vegetation Index (NDVI), land cover (built and bare land, water, or vegetation), latitude, longitude, and week of the year. Results The model explained 77% of the variance in surface temperature, accounting for both temporal and spatial variations. The standard error of estimates was 1.42°C. Land cover and NDVI were strong predictors of surface temperature. Conclusions This study suggests that a statistical approach to estimating surface temperature incorporating both spatially explicit satellite data and time-varying meteorological data may be relevant to assessing exposure to heat during the warm season in the Quebec. By allowing the estimation of space- and time-specific surface temperatures, this model may also be used to assess the possible impacts of land use changes under various meteorological conditions. It can be applied to assess heat exposure within a large population and at relatively fine-grained scale. It may be used to evaluate the acute health effect of heat exposure over long time frames. The method proposed here could be replicated in other areas around the globe for which satellite data and meteorological data is available. PMID:21251286

A modeling study on the effect of urban land surface forcing to regional meteorology and air quality over South China

NASA Astrophysics Data System (ADS)

Zhu, Kuanguang; Xie, Min; Wang, Tijian; Cai, Junxiong; Li, Songbing; Feng, Wen

2017-03-01

The change of land-use from natural to artificial surface induced by urban expansion can deeply impact the city environment. In this paper, the model WRF/Chem is applied to explore the effect of this change on regional meteorology and air quality over South China, where people have witnessed a rapid rate of urbanization. Two sets of urban maps are adopted to stand for the pre-urbanization and the present urban land-use distributions. Month-long simulations are conducted for January and July, 2014. The results show that urban expansion can obviously change the weather conditions around the big cities of South China. Especially in the Pearl River Delta region (PRD), the urban land-use change can increase the sensible heat flux by 40 W/m2 in January and 80 W/m2 in July, while decrease the latent heat flux about -50 W/m2 in January and -120 W/m2 in July. In the consequent, 2-m air temperature (T2) increases as much as 1 °C and 2 °C (respective to January and July), planetary boundary layer height (PBLH) rises up by 100-150 m and 300 m, 10-m wind speed (WS10) decreases by -1.2 m/s and -0.3 m/s, and 2-m specific humidity is reduced by -0.8 g/kg and -1.5 g/kg. Also, the precipitation in July can be increased as much as 120 mm, with more heavy rains and rainstorms. These variations of meteorological factors can significantly impact the spatial and vertical distribution of air pollutants as well. In PRD, the enhanced updraft can reduce the surface concentrations of PM10 by -40 μg/m3 (30%) in January and -80 μg/m3 (50%) in July, but produce a correlating increase in the concentrations at higher atmospheric layers. However, according to the increase in T2 and the decrease in surface NO, the surface concentrations of O3 in PRD can increase by 2-6 ppb in January and 8-12 ppb in July. Meanwhile, there is a significant increase in the O3 concentrations at upper layers above PRD, which should be attributed to the increase in air temperature and the enhanced upward transport of O3 and its precursors. As for some relative small cities, such as Haikou, there is very little variation in surface PM10 and O3 in both months, implying less urbanization in these areas. Moreover, the depletion of O3 by NO may be the main cause of the reduction of O3 at upper layers in these small cities.

Spatio-Temporal Variation and Futuristic Emission Scenario of Ambient Nitrogen Dioxide over an Urban Area of Eastern India Using GIS and Coupled AERMOD-WRF Model.

PubMed

Dey, Sharadia; Gupta, Srimanta; Sibanda, Precious; Chakraborty, Arun

2017-01-01

The present study focuses on the spatio-temporal variation of nitrogen dioxide (NO2) during June 2013 to May 2015 and its futuristic emission scenario over an urban area (Durgapur) of eastern India. The concentration of ambient NO2 shows seasonal as well as site specific characteristics. The site with high vehicular density (Muchipara) shows highest NO2 concentration followed by industrial site (DVC- DTPS Colony) and the residential site (B Zone), respectively. The seasonal variation of ambient NO2 over the study area is portrayed by means of Geographical Information System based Digital Elevation Model. Out of the total urban area under consideration (114.982 km2), the concentration of NO2 exceeded the National Ambient Air Quality Standard (NAAQS) permissible limit over an area of 5.000 km2, 0.786 km2 and 0.653 km2 in post monsoon, winter and pre monsoon, respectively. Wind rose diagrams, correlation and regression analyses show that meteorology plays a crucial role in dilution and dispersion of NO2 near the earth's surface. Principal component analysis identifies vehicular source as the major source of NO2 in all the seasons over the urban region. Coupled AMS/EPA Regulatory Model (AERMOD)-Weather Research and Forecasting (WRF) model is used for predicting the concentration of NO2. Comparison of the observed and simulated data shows that the model overestimates the concentration of NO2 in all the seasons (except winter). The results show that coupled AERMOD-WRF model can overcome the unavailability of hourly surface as well as upper air meteorological data required for predicting the pollutant concentration, but improvement of emission inventory along with better understanding of the sinks and sources of ambient NO2 is essential for capturing the more realistic scenario.

Spatio-Temporal Variation and Futuristic Emission Scenario of Ambient Nitrogen Dioxide over an Urban Area of Eastern India Using GIS and Coupled AERMOD–WRF Model

PubMed Central

Dey, Sharadia; Gupta, Srimanta; Sibanda, Precious; Chakraborty, Arun

2017-01-01

The present study focuses on the spatio-temporal variation of nitrogen dioxide (NO2) during June 2013 to May 2015 and its futuristic emission scenario over an urban area (Durgapur) of eastern India. The concentration of ambient NO2 shows seasonal as well as site specific characteristics. The site with high vehicular density (Muchipara) shows highest NO2 concentration followed by industrial site (DVC- DTPS Colony) and the residential site (B Zone), respectively. The seasonal variation of ambient NO2 over the study area is portrayed by means of Geographical Information System based Digital Elevation Model. Out of the total urban area under consideration (114.982 km2), the concentration of NO2 exceeded the National Ambient Air Quality Standard (NAAQS) permissible limit over an area of 5.000 km2, 0.786 km2 and 0.653 km2 in post monsoon, winter and pre monsoon, respectively. Wind rose diagrams, correlation and regression analyses show that meteorology plays a crucial role in dilution and dispersion of NO2 near the earth’s surface. Principal component analysis identifies vehicular source as the major source of NO2 in all the seasons over the urban region. Coupled AMS/EPA Regulatory Model (AERMOD)–Weather Research and Forecasting (WRF) model is used for predicting the concentration of NO2. Comparison of the observed and simulated data shows that the model overestimates the concentration of NO2 in all the seasons (except winter). The results show that coupled AERMOD–WRF model can overcome the unavailability of hourly surface as well as upper air meteorological data required for predicting the pollutant concentration, but improvement of emission inventory along with better understanding of the sinks and sources of ambient NO2 is essential for capturing the more realistic scenario. PMID:28141866

Connecting Urbanization to Precipitation: the case of Mexico City

NASA Astrophysics Data System (ADS)

Georgescu, Matei

2017-04-01

Considerable evidence exists illustrating the influence of urban environments on precipitation. We revisit this theme of significant interest to a broad spectrum of disciplines ranging from urban planning to engineering to urban numerical modeling and climate, by detailing the simulated effect of Mexico City's built environment on regional precipitation. Utilizing the Weather Research and Forecasting (WRF) system to determine spatiotemporal changes in near-surface air temperature, precipitation, and boundary layer conditions induced by the modern-day urban landscape relative to presettlement conditions, I mechanistically link the built environment-induced increase in air temperature to simulated increases in rainfall during the evening hours. This simulated increase in precipitation is in agreement with historical observations documenting observed rainfall increase. These results have important implications for understanding the meteorological conditions leading to the widespread and recurrent urban flooding that continues to plague the Mexico City Metropolitan Area.

Characterization and Scaling of Black Carbon Aerosol Concentration with City Population Based on In-Situ Measurements and Analysis

NASA Astrophysics Data System (ADS)

Paredes-Miranda, G.; Arnott, W. P.; Moosmuller, H.

2010-12-01

The global trend toward urbanization and the resulting increase in city population has directed attention toward air pollution in megacities. A closely related question of importance for urban planning and attainment of air quality standards is how pollutant concentrations scale with city population. In this study, we use measurements of light absorption and light scattering coefficients as proxies for primary (i.e., black carbon; BC) and total (i.e., particulate matter; PM) pollutant concentration, to start addressing the following questions: What patterns and generalizations are emerging from our expanding data sets on urban air pollution? How does the per-capita air pollution vary with economic, geographic, and meteorological conditions of an urban area? Does air pollution provide an upper limit on city size? Diurnal analysis of black carbon concentration measurements in suburban Mexico City, Mexico, Las Vegas, NV, USA, and Reno, NV, USA for similar seasons suggests that commonly emitted primary air pollutant concentrations scale approximately as the square root of the urban population N, consistent with a simple 2-d box model. The measured absorption coefficient Babs is approximately proportional to the BC concentration (primary pollution) and thus scales with the square root of population (N). Since secondary pollutants form through photochemical reactions involving primary pollutants, they scale also with square root of N. Therefore the scattering coefficient Bsca, a proxy for PM concentration is also expected to scale with square root of N. Here we present light absorption and scattering measurements and data on meteorological conditions and compare the population scaling of these pollutant measurements with predictions from the simple 2-d box model. We find that these basin cities are connected by the square root of N dependence. Data from other cities will be discussed as time permits.

The MUMBA campaign: measurements of urban, marine and biogenic air

NASA Astrophysics Data System (ADS)

Paton-Walsh, Clare; Guérette, Élise-Andrée; Kubistin, Dagmar; Humphries, Ruhi; Wilson, Stephen R.; Dominick, Doreena; Galbally, Ian; Buchholz, Rebecca; Bhujel, Mahendra; Chambers, Scott; Cheng, Min; Cope, Martin; Davy, Perry; Emmerson, Kathryn; Griffith, David W. T.; Griffiths, Alan; Keywood, Melita; Lawson, Sarah; Molloy, Suzie; Rea, Géraldine; Selleck, Paul; Shi, Xue; Simmons, Jack; Velazco, Voltaire

2017-06-01

The Measurements of Urban, Marine and Biogenic Air (MUMBA) campaign took place in Wollongong, New South Wales (a small coastal city approximately 80 km south of Sydney, Australia) from 21 December 2012 to 15 February 2013. Like many Australian cities, Wollongong is surrounded by dense eucalyptus forest, so the urban airshed is heavily influenced by biogenic emissions. Instruments were deployed during MUMBA to measure the gaseous and aerosol composition of the atmosphere with the aim of providing a detailed characterisation of the complex environment of the ocean-forest-urban interface that could be used to test the skill of atmospheric models. The gases measured included ozone, oxides of nitrogen, carbon monoxide, carbon dioxide, methane and many of the most abundant volatile organic compounds. The aerosol characterisation included total particle counts above 3 nm, total cloud condensation nuclei counts, mass concentration, number concentration size distribution, aerosol chemical analyses and elemental analysis.The campaign captured varied meteorological conditions, including two extreme heat events, providing a potentially valuable test for models of future air quality in a warmer climate. There was also an episode when the site sampled clean marine air for many hours, providing a useful additional measure of the background concentrations of these trace gases within this poorly sampled region of the globe. In this paper we describe the campaign, the meteorology and the resulting observations of atmospheric composition in general terms in order to equip the reader with a sufficient understanding of the Wollongong regional influences to use the MUMBA datasets as a case study for testing a chemical transport model. The data are available from PANGAEA (http://doi.pangaea.de/10.1594/PANGAEA.871982).

Urban Surface Radiative Energy Budgets Determined Using Aircraft Scanner Data

NASA Technical Reports Server (NTRS)

Luvall, Jeffrey C.; Quattrochi, Dale A.; Rickman, Doug L.; Estes, Maury G.; Arnold, James E. (Technical Monitor)

2002-01-01

It is estimated that by the year 2025, 80% of the world's population will live in cities. The extent of these urban areas across the world can be seen in an image of city lights from the Defense Meteorological Satellite Program. In many areas of North America and Europe, it is difficult to separate individual cities because of the dramatic growth and sprawl of urbanized areas. This conversion of the natural landscape vegetation into man-made urban structures such as roads and buildings drastically alter the regional surface energy budgets, hydrology, precipitation patterns, and meteorology. One of the earliest recognized and measured phenomena of urbanization is the urban heat island (UHI) which was reported as early as 1833 for London and 1862 for Paris. The urban heat island results from the energy that is absorbed by man-made materials during the day and is released at night resulting in the heating of the air within the urban area. The magnitude of the air temperature difference between the urban and surrounding countryside is highly dependent on the structure of the urban area, amount of solar immolation received during the day, and atmospheric conditions during the night. These night time air temperature differences can be in the range of 2 to 5 C. or greater. Although day time air temperature differences between urban areas and the countryside exists during the day, atmospheric mixing and stability reduce the magnitude. This phenomena is not limited to large urban areas, but also occurs in smaller metropolitan areas. The UHI has significant impacts on the urban air quality, meteorology, energy use, and human health. The UPI can be mitigated through increasing the amount of vegetation and modification of urban surfaces using high albedo materials for roofs and paved surfaces. To understand why the urban heat island phenomenon exists it is useful to define the surface in terms of the surface energy budget. Surface temperature and albedo is a major component of the surface energy budget. Knowledge of it is important in any attempt to describe the radiative and mass fluxes which occur at the surface. Use of energy terms in modeling surface energy budgets allows the direct comparison of various land surfaces encountered in a urban landscape, from vegetated (forest and herbaceous) to non-vegetated (bare soil, roads, and buildings). These terms are also easily measured using remote sensing from aircraft or satellite platforms allowing one to examine the spacial variability. The partitioning of energy budget terms depends on the surface type. In natural landscapes, the partitioning is dependent on canopy biomass, leaf area index, aerodynamic roughness, and moisture status, all of which are influenced by the development stage of the ecosystem. In urban landscapes, coverage by man-made materials substantially alters the surface face energy budget. The remotely sensed data obtained from aircraft and satellites, when properly calibrated allows the measurement of important terms in the radiative surface energy budget a urban landscape scale.

Integrating local urban climate modelling and mobile sensor data for personal exposure assessments in the context of urban heat island effect

NASA Astrophysics Data System (ADS)

Ueberham, Maximilian; Hertel, Daniel; Schlink, Uwe

2017-04-01

Deeper knowledge about urban climate conditions is getting more important in the context of climate change, urban population growth, urban compaction and continued surface sealing. Especially the urban heat island effect (UHI) is one of the most significant human induced alterations of Earth's surface climate. According to this the appearance frequency of heat waves in cities will increase with deep impacts on personal thermal comfort, human health and local residential quality of citizens. UHI can be very heterogenic within a city and research needs to focus more on the neighborhood scale perspective to get further insights about the heat burden of individuals. However, up to now, few is known about local thermal environmental variances and personal exposure loads. To monitor these processes and the impact on individuals, improved monitoring approaches are crucial, complementing data recorded at conventional fixed stations. Therefore we emphasize the importance of micro-meteorological modelling and mobile measurements to shed new light on the nexus of urban human-climate interactions. Contributing to this research we jointly present the approaches of our two PhD-projects. Firstly we illustrate on the basis of an example site, how local thermal conditions in an urban district can be simulated and predicted by a micro-meteorological model. Secondly we highlight the potentials of personal exposure measurements based on an evaluation of mobile micro-sensing devices (MSDs) and analyze and explain differences between model predictions and mobile records. For the examination of local thermal conditions we calculated ENVI-met simulations within the "Bayerischer Bahnhof" quarter in Leipzig (Saxony, Germany; 51°20', 12°22'). To accomplish the maximum temperature contrasts within the diverse built-up structures we chose a hot summer day (25 Aug 2016) under autochthonous weather conditions. From these simulations we analyzed a UHI effect between the model core (urban area) and the surrounding nesting area (rural area). Preparing for the outdoor application of mobile MSDs we tested their accuracy and performance between several MSDs and reliable sophisticated devices under laboratory conditions. We found that variations mainly depend on the device design and technology (e.g. active/passive ventilation). The standard deviation of the temperature records was quite stable over the whole range of values and the MSDs proved to be applicable for the purpose of our study. In conclusion the benefit of integrating mobile data and micrometeorological predictions is manifold. Mobile data can be used for the investigation of personal exposure in the context of heat stress and for the verification and training of micrometeorological models. Otherwise, model predictions can identify local areas of special climate interest where additional mobile measurements would be beneficial to provide new information for mitigation and adaptation actions.

The model SIRANE for atmospheric urban pollutant dispersion; part I, presentation of the model

NASA Astrophysics Data System (ADS)

Soulhac, Lionel; Salizzoni, Pietro; Cierco, F.-X.; Perkins, Richard

2011-12-01

In order to control and manage urban air quality, public authorities require an integrated approach that incorporates direct measurements and modelling of mean pollutant concentrations. These have to be performed by means of operational modelling tools, that simulate the transport of pollutants within and above the urban canopy over a large number of streets. The operational models must be able to assess rapidly a large variety of situations and with limited computing resources. SIRANE is an operational urban dispersion model based on a simplified description of the urban geometry that adopts parametric relations for the pollutant transfer phenomena within and out of the urban canopy. The streets in a city district are modelled as a network of connected street segments. The flow within each street is driven by the component of the external wind parallel to the street, and the pollutant is assumed to be uniformly mixed within the street. The model contains three main mechanisms for transport in and out of a street: advection along the street axis, diffusion across the interface between the street and the overlying air flow and exchanges with other streets at street intersections. The dispersion of pollutants advected or diffused out of the streets is taken into account using a Gaussian plume model, with the standard deviations σ y and σ z parameterised by the similarity theory. The input data for the final model are the urban geometry, the meteorological parameters, the background concentration of pollutants advected into the model domain by the wind and the emissions within each street in the network.

Urban and regional land use analysis: CARETS and census cities experiment package

NASA Technical Reports Server (NTRS)

Alexander, R. (Principal Investigator); Lins, H. F., Jr.; Gallagher, D. B.

1975-01-01

The author has identified the following significant results. Temperatures in degrees Celsius were derived from PCM counts using the Pease's modified gray window technique. The Outcalt simulator was setup on the USGS computer. The input data to the model are basically meteorological and geographical in nature. The output data is presented in three matrices.

Project ATLANTA (Atlanta Land use Analysis: Temperature and Air Quality): Use of Remote Sensing and Modeling to Analyze How Urban Land Use Change Affects Meteorology and Air Quality Through Time

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.; Estes, Maurice G., Jr.

1999-01-01

This paper presents an overview of Project ATLANTA (ATlanta Land use ANalysis: Temperature and Air-quality) which is an investigation that seeks to observe, measure, model, and analyze how the rapid growth of the Atlanta, Georgia metropolitan area since the early 1970's has impacted the region's climate and air quality. The primary objectives for this research effort are: (1) To investigate and model the relationships between land cover change in the Atlanta metropolitan, and the development of the urban heat island phenomenon through time; (2) To investigate and model the temporal relationships between Atlanta urban growth and land cover change on air quality; and (3) To model the overall effects of urban development on surface energy budget characteristics across the Atlanta urban landscape through time. Our key goal is to derive a better scientific understanding of how land cover changes associated with urbanization in the Atlanta area, principally in transforming forest lands to urban land covers through time, has, and will, effect local and regional climate, surface energy flux, and air quality characteristics. Allied with this goal is the prospect that the results from this research can be applied by urban planners, environmental managers and other decision-makers, for determining how urbanization has impacted the climate and overall environment of the Atlanta area. Multiscaled remote sensing data, particularly high resolution thermal infrared data, are integral to this study for the analysis of thermal energy fluxes across the Atlanta urban landscape.

Modeling and evaluation of urban pollution events of atmospheric heavy metals from a large Cu-smelter.

PubMed

Chen, Bing; Stein, Ariel F; Castell, Nuria; Gonzalez-Castanedo, Yolanda; Sanchez de la Campa, A M; de la Rosa, J D

2016-01-01

Metal smelting and processing are highly polluting activities that have a strong influence on the levels of heavy metals in air, soil, and crops. We employ an atmospheric transport and dispersion model to predict the pollution levels originated from the second largest Cu-smelter in Europe. The model predicts that the concentrations of copper (Cu), zinc (Zn), and arsenic (As) in an urban area close to the Cu-smelter can reach 170, 70, and 30 ng m−3, respectively. The model captures all the observed urban pollution events, but the magnitude of the elemental concentrations is predicted to be lower than that of the observed values; ~300, ~500, and ~100 ng m−3 for Cu, Zn, and As, respectively. The comparison between model and observations showed an average correlation coefficient of 0.62 ± 0.13. The simulation shows that the transport of heavy metals reaches a peak in the afternoon over the urban area. The under-prediction in the peak is explained by the simulated stronger winds compared with monitoring data. The stronger simulated winds enhance the transport and dispersion of heavy metals to the regional area, diminishing the impact of pollution events in the urban area. This model, driven by high resolution meteorology (2 km in horizontal), predicts the hourly-interval evolutions of atmospheric heavy metal pollutions in the close by urban area of industrial hotspot.

Urban-rural fog differences in Belgrade area, Serbia

NASA Astrophysics Data System (ADS)

Vujović, Dragana; Todorović, Nedeljko

2018-02-01

Urban/rural fog appearance during the last 27 years in the Belgrade region is analysed using hourly meteorological records from two meteorological stations: an urban station at Belgrade-Vračar (BV) and a rural station at Belgrade-Airport (BA). The effects of urban development on fog formation are discussed through analysis of fog frequency trends and comparison with a number of meteorological parameters. The mean annual and the mean annual minimum temperatures were greater at the urban BV station than at the rural BA station. The mean monthly relative humidity and the mean monthly water vapour pressure were greater at the rural than urban station. During the period of research (1988-2014), BA experiences 425 more days with fog than BV, which means that BV experiences fog for 62.68% of foggy days at BA. Trends in the number of days with fog were statistically non-significant. We analysed the fog occurrence during different types of weather. Fog in urban BV occurred more frequently during cyclonal circulation (in 52.75% of cases). In rural BA, the trend was the opposite and fog appeared more frequently during anticyclonic circulation (in 53.58% of cases). Fog at BV occurred most frequently in stable anticyclonic weather with light wind, when a temperature inversion existed (21.86% of cases). Most frequently, fog at BA occurred in the morning and only lasted a short time, followed by clearer skies during the anticyclonic warm and dry weather (22.55% of cases).

Temporal modelling and forecasting of the airborne pollen of Cupressaceae on the southwestern Iberian Peninsula.

PubMed

Silva-Palacios, Inmaculada; Fernández-Rodríguez, Santiago; Durán-Barroso, Pablo; Tormo-Molina, Rafael; Maya-Manzano, José María; Gonzalo-Garijo, Ángela

2016-02-01

Cupressaceae includes species cultivated as ornamentals in the urban environment. This study aims to investigate airborne pollen data for Cupressaceae on the southwestern Iberian Peninsula over a 21-year period and to analyse the trends in these data and their relationship with meteorological parameters using time series analysis. Aerobiological sampling was conducted from 1993 to 2013 in Badajoz (SW Spain). The main pollen season for Cupressaceae lasted, on average, 58 days, ranging from 55 to 112 days, from 24 January to 22 March. Furthermore, a short-term forecasting model has been developed for daily pollen concentrations. The model proposed to forecast the airborne pollen concentration is described by one equation. This expression is composed of two terms: the first term represents the pollen concentration trend in the air according to the average concentration of the previous 10 days; the second term is obtained from considering the actual pollen concentration value, which is calculated based on the most representative meteorological parameters multiplied by a fitting coefficient. Temperature was the main meteorological factor by its influence over daily pollen forecast, being the rain the second most important factor. This model represents a good approach to a continuous balance model of Cupressaceae pollen concentration and is supported by a close agreement between the observed and predicted mean concentrations. The novelty of the proposed model is the analysis of meteorological parameters that are not frequently used in Aerobiology.

Urban amplification of the global warming in Moscow megacity

NASA Astrophysics Data System (ADS)

Kislov, Alexander; Konstantinov, Pavel; Varentsov, Mikhail; Samsonov, Timofey; Gorlach, Irina; Trusilova, Kristina

2015-04-01

Climate changes in the large cities are very important and requires better understanding. The focus of this paper is climate change of the Moscow megacity. Its urban features strongly influence the atmospheric boundary layer above the Moscow agglomeration area and determine the microclimatic features of the local environment, such as urban heat island (UHI). Available meteorological observations within the Moscow urban area and surrounding territory allow us to assess the natural climate variations and human-induced climate warming separately. To obtain more precisely viewing on the UHI structure we have included into the analysis the satellite data (Meteosat-10), providing temperature and humidity profiles with high resolution. To investigate the mechanism of the urban amplification we realized the regional climate model COSMO-CLM+TEB. Apart from detailed climate research the model runs will be planned for climate projecting of Moscow agglomeration area. Climate change differences between urban and rural areas are determined by changes of the shape of the UHI and their relationships with changes of building height and density. Therefore, the urban module of COSMO-CLM+TEB model is fed by information from special GIS database contenting both geometric characteristics of the urban canyons and other characteristics of the urban surface. The sources of information were maps belonging to the OpenStreetMap, and digital elevation models SRTM90 and ASTER GDEM v.2 as well. The multiscale GIS database allows us to generate such kind of information with different spatial resolution (200, 500 and 1000 meters).

Emission Inventory Development and Application Based On an Atmospheric Emission Source Priority Control Classification Technology Method, a Case Study in the Middle Reaches of Yangtze River Urban Agglomerations, China

NASA Astrophysics Data System (ADS)

Sun, X.; Cheng, S.

2017-12-01

This paper presents the first attempt to investigate the emission source control of the Middle Reaches of Yangtze River Urban Agglomerations (MRYRUA), one of the national urban agglomerations in China. An emission inventory of the MRYRUA was the first time to be developed as inputs to the CAMx model based on county-level activity data obtained by full-coverage investigation and source-based spatial surrogates. The emission inventory was proved to be acceptable owing to the atmospheric modeling verification. A classification technology method for atmospheric pollution source priority control was the first time to be introduced and applied in the MRYRUA for the evaluation of the emission sources control on the region-scale and city-scale. MICAPS (Meteorological Information comprehensive Analysis and Processing System) was applied for the regional meteorological condition and sensitivity analysis. The results demonstrated that the emission sources in the Hefei-center Urban Agglomerations contributed biggest on the mean PM2.5 concentrations of the MRYRUA and should be taken the priority to control. The emission sources in the Ma'anshan city, Xiangtan city, Hefei city and Wuhan city were the bigger contributors on the mean PM2.5 concentrations of the MRYRUA among the cities and should be taken the priority to control. In addition, the cities along the Yangtze River and the tributary should be given the special attention for the regional air quality target attainments. This study provide a valuable preference for policy makers to develop effective air pollution control strategies.

Urban air quality assessment using monitoring data of fractionized aerosol samples, chemometrics and meteorological conditions.

PubMed

Yotova, Galina I; Tsitouridou, Roxani; Tsakovski, Stefan L; Simeonov, Vasil D

2016-01-01

The present article deals with assessment of urban air by using monitoring data for 10 different aerosol fractions (0.015-16 μm) collected at a typical urban site in City of Thessaloniki, Greece. The data set was subject to multivariate statistical analysis (cluster analysis and principal components analysis) and, additionally, to HYSPLIT back trajectory modeling in order to assess in a better way the impact of the weather conditions on the pollution sources identified. A specific element of the study is the effort to clarify the role of outliers in the data set. The reason for the appearance of outliers is strongly related to the atmospheric condition on the particular sampling days leading to enhanced concentration of pollutants (secondary emissions, sea sprays, road and soil dust, combustion processes) especially for ultra fine and coarse particles. It is also shown that three major sources affect the urban air quality of the location studied-sea sprays, mineral dust and anthropogenic influences (agricultural activity, combustion processes, and industrial sources). The level of impact is related to certain extent to the aerosol fraction size. The assessment of the meteorological conditions leads to defining of four downwind patterns affecting the air quality (Pelagic, Western and Central Europe, Eastern and Northeastern Europe and Africa and Southern Europe). Thus, the present study offers a complete urban air assessment taking into account the weather conditions, pollution sources and aerosol fractioning.

Built Expansion and Global Climate Change Drive Projected Urban Heat: Relative Magnitudes, Interactions, and Mitigation

NASA Astrophysics Data System (ADS)

Krayenhoff, E. S.; Georgescu, M.; Moustaoui, M.

2016-12-01

Surface climates are projected to warm due to global climate change over the course of the 21st century, and demographic projections suggest urban areas in the United States will continue to expand and develop, with associated local climate outcomes. Interactions between these two drivers of urban heat have not been robustly quantified to date. Here, simulations with the Weather Research and Forecasting model (coupled to a Single-Layer Urban Canopy Model) are performed at 20 km resolution over the continental U.S. for two 10-year periods: contemporary (2000-2009) and end-of-century (2090-2099). Present and end of century urban land use are derived from the Environmental Protection Agency's Integrated Climate and Land-Use Scenarios. Modelled effects on urban climates are evaluated regionally. Sensitivity to climate projection (Community Climate System Model 4.0, RCP 4.5 vs. RCP 8.5) and associated urban development scenarios are assessed. Effects on near-surface urban air temperature of RCP8.5 climate change are greater than those attributable to the corresponding urban development in many regions. Interaction effects vary by region, and while of lesser magnitude, are not negligible. Moreover, urban development and its interactions with RCP8.5 climate change modify the distribution of convective precipitation over the eastern US. Interaction effects result from the different meteorological effects of urban areas under current and future climate. Finally, the potential for design implementations such as green roofs and high albedo roofs to offset the projected warming is considered. Impacts of these implementations on precipitation are also assessed.

Inland and coastal flooding: developments in prediction and prevention.

PubMed

Hunt, J C R

2005-06-15

We review the scientific and engineering understanding of various types of inland and coastal flooding by considering the different causes and dynamic processes involved, especially in extreme events. Clear progress has been made in the accuracy of numerical modelling of meteorological causes of floods, hydraulics of flood water movement and coastal wind-wave-surge. Probabilistic estimates from ensemble predictions and the simultaneous use of several models are recent techniques in meteorological prediction that could be considered for hydraulic and oceanographic modelling. The contribution of remotely sensed data from aircraft and satellites is also considered. The need to compare and combine statistical and computational modelling methodologies for long range forecasts and extreme events is emphasized, because this has become possible with the aid of kilometre scale computations and network grid facilities to simulate and analyse time-series and extreme events. It is noted that despite the adverse effects of climatic trends on flooding, appropriate planning of rapidly growing urban areas could mitigate some of the worst effects. However, resources for flood prevention, including research, have to be considered in relation to those for other natural disasters. Policies have to be relevant to the differing geology, meteorology and cultures of the countries affected.

Simulation of summer ozone episodes in Southeast Louisiana during 2006-2015

NASA Astrophysics Data System (ADS)

Guo, H.; Zhang, H.

2017-12-01

Southeast Louisiana experiences high ozone (O3) events due to immense emissions from industrial and urban sources and unique meteorology conditions of high temperatures, intensive solar radiation and land-sea breeze circulation. The Community Multi-scale Air Quality (CMAQ) model with modified photochemical mechanism is used to investigate the contributions of regional transport to ozone (O3) and its precursors to Southeast Louisiana in summer months from 2006 to 2015. The meteorological and CMAQ model performance are validated. Spatial and temporal variations of O3 are investigated during summer episodes in 10 years. Contributions of different source types and regions to 1 hour O3 are also quantified. Changes in the contributions of different source types and regions are also obtained to help design intelligent control measures.

Quantification and mapping of urban fluxes under climate change: Application of WRF-SUEWS model to Greater Porto area (Portugal)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rafael, S., E-mail: sandra.rafael@ua.pt

Climate change and the growth of urban populations are two of the main challenges facing Europe today. These issues are linked as climate change results in serious challenges for cities. Recent attention has focused on how urban surface-atmosphere exchanges of heat and water will be affected by climate change and the implications for urban planning and sustainability. In this study energy fluxes for Greater Porto area, Portugal, were estimated and the influence of the projected climate change evaluated. To accomplish this, the Weather Research and Forecasting Model (WRF) and the Surface Urban Energy and Water Balance Scheme (SUEWS) were appliedmore » for two climatological scenarios: a present (or reference, 1986–2005) scenario and a future scenario (2046–2065), in this case the Representative Concentration Pathway RCP8.5, which reflects the worst set of expectations (with the most onerous impacts). The results show that for the future climate conditions, the incoming shortwave radiation will increase by around 10%, the sensible heat flux around 40% and the net storage heat flux around 35%. In contrast, the latent heat flux will decrease about 20%. The changes in the magnitude of the different fluxes result in an increase of the net all-wave radiation by 15%. The implications of the changes of the energy balance on the meteorological variables are discussed, particularly in terms of temperature and precipitation. - Highlights: • Assessment of energy fluxes behaviour under past period and medium-term climate change projection. • Evaluation of climate change at urban scale. • Meteorological variables alters the partitioning of the energy fluxes. • Changes in the partition of the annual energy balance are found between the two analysed periods. • Increase in the magnitude of sensible and storage heat fluxes.« less

Coupling meteorology, metal concentrations, and Pb isotopes for source attribution in archived precipitation samples.

PubMed

Graney, Joseph R; Landis, Matthew S

2013-03-15

A technique that couples lead (Pb) isotopes and multi-element concentrations with meteorological analysis was used to assess source contributions to precipitation samples at the Bondville, Illinois USA National Trends Network (NTN) site. Precipitation samples collected over a 16month period (July 1994-October 1995) at Bondville were parsed into six unique meteorological flow regimes using a minimum variance clustering technique on back trajectory endpoints. Pb isotope ratios and multi-element concentrations were measured using high resolution inductively coupled plasma-sector field mass spectrometry (ICP-SFMS) on the archived precipitation samples. Bondville is located in central Illinois, ~250km downwind from smelters in southeast Missouri. The Mississippi Valley Type ore deposits in Missouri provided a unique multi-element and Pb isotope fingerprint for smelter emissions which could be contrasted to industrial emissions from the Chicago and Indianapolis urban areas (~125km north and east, of Bondville respectively) and regional emissions from electric utility facilities. Differences in Pb isotopes and element concentrations in precipitation corresponded to flow regime. Industrial sources from urban areas, and thorogenic Pb from coal use, could be differentiated from smelter emissions from Missouri by coupling Pb isotopes with variations in element ratios and relative mass factors. Using a three endmember mixing model based on Pb isotope ratio differences, industrial processes in urban airsheds contributed 56±19%, smelters in southeast Missouri 26±13%, and coal combustion 18±7%, of the Pb in precipitation collected in Bondville in the mid-1990s. Copyright © 2012 Elsevier B.V. All rights reserved.

“Fine-Scale Application of the coupled WRF-CMAQ System to ...

EPA Pesticide Factsheets

The DISCOVER-AQ project (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality), is a joint collaboration between NASA, U.S. EPA and a number of other local organizations with the goal of characterizing air quality in urban areas using satellite, aircraft, vertical profiler and ground based measurements (http://discover-aq.larc.nasa.gov). In July 2011, the DISCOVER-AQ project conducted intensive air quality measurements in the Baltimore, MD and Washington, D.C. area in the eastern U.S. To take advantage of these unique data, the Community Multiscale Air Quality (CMAQ) model, coupled with the Weather Research and Forecasting (WRF) model is used to simulate the meteorology and air quality in the same region using 12-km, 4-km and 1-km horizontal grid spacings. The goal of the modeling exercise is to demonstrate the capability of the coupled WRF-CMAQ modeling system to simulate air quality at fine grid spacings in an urban area. Development of new data assimilation techniques and the use of higher resolution input data for the WRF model have been implemented to improve the meteorological results, particularly at the 4-km and 1-km grid resolutions. In addition, a number of updates to the CMAQ model were made to enhance the capability of the modeling system to accurately represent the magnitude and spatial distribution of pollutants at fine model resolutions. Data collected during the 2011 DISCOVER-AQ campa

“Application and evaluation of the two-way coupled WRF ...

EPA Pesticide Factsheets

The DISCOVER-AQ project (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality), is a joint collaboration between NASA, U.S. EPA and a number of other local organizations with the goal of characterizing air quality in urban areas using satellite, aircraft, vertical profiler and ground based measurements (http://discover-aq.larc.nasa.gov). In July 2011, the DISCOVER-AQ project conducted intensive air quality measurements in the Baltimore, MD and Washington, D.C. area in the eastern U.S. To take advantage of these unique data, the Community Multiscale Air Quality (CMAQ) model, coupled with the Weather Research and Forecasting (WRF) model is used to simulate the meteorology and air quality in the same region using 12-km, 4-km and 1-km horizontal grid spacings. The goal of the modeling exercise is to demonstrate the capability of the coupled WRF-CMAQ modeling system to simulate air quality at fine grid spacings in an urban area. Development of new data assimilation techniques and the use of higher resolution input data for the WRF model have been implemented to improve the meteorological results, particularly at the 4-km and 1-km grid resolutions. In addition, a number of updates to the CMAQ model were made to enhance the capability of the modeling system to accurately represent the magnitude and spatial distribution of pollutants at fine model resolutions. Data collected during the 2011 DISCOVER-AQ campa

Meteorological Modeling of Wintertime Cold Air Pool Stagnation Episodes in the Uintah and Salt Lake Basins

NASA Astrophysics Data System (ADS)

Crosman, E.; Horel, J.; Blaylock, B. K.; Foster, C.

2014-12-01

High wintertime ozone concentrations in rural areas associated with oil and gas development and high particulate concentrations in urban areas have become topics of increasing concern in the Western United States, as both primary and secondary pollutants become trapped within stable wintertime boundary layers. While persistent cold air pools that enable such poor wintertime air quality are typically associated with high pressure aloft and light winds, the complex physical processes that contribute to the formation, maintenance, and decay of persistent wintertime temperature inversions are only partially understood. In addition, obtaining sufficiently accurate numerical weather forecasts and meteorological simulations of cold air pools for input into chemical models remains a challenge. This study examines the meteorological processes associated with several wintertime pollution episodes in Utah's Uintah and Salt Lake Basins using numerical Weather Research and Forecasting model simulations and observations collected from the Persistent Cold Air Pool and Uintah Basin Ozone Studies. The temperature, vertical structure, and winds within these cold air pools was found to vary as a function of snow cover, snow albedo, land use, cloud cover, large-scale synoptic flow, and episode duration. We evaluate the sensitivity of key atmospheric features such as stability, planetary boundary layer depth, local wind flow patterns and transport mechanisms to variations in surface forcing, clouds, and synoptic flow. Finally, noted deficiencies in the meteorological models of cold air pools and modifications to the model snow and microphysics treatment that have resulted in improved cold pool simulations will be presented.

High resolution modeling of a small urban catchment

NASA Astrophysics Data System (ADS)

Skouri-Plakali, Ilektra; Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel

2016-04-01

Flooding is one of the most complex issues that urban environments have to deal with. In France, flooding remains the first natural risk with 72% of decrees state of natural disaster issued between October 1982 and mid-November 2014. Flooding is a result of meteorological extremes that are usually aggravated by the hydrological behavior of urban catchments and human factors. The continuing urbanization process is indeed changing the whole urban water cycle by limiting the infiltration and promoting runoff. Urban environments are very complex systems due to their extreme variability, the interference between human activities and natural processes but also the effect of the ongoing urbanization process that changes the landscape and hardly influences their hydrologic behavior. Moreover, many recent works highlight the need to simulate all urban water processes at their specific temporal and spatial scales. However, considering urban catchments heterogeneity still challenging for urban hydrology, even after advances noticed in term of high-resolution data collection and computational resources. This issue is more to be related to the architecture of urban models being used and how far these models are ready to take into account the extreme variability of urban catchments. In this work, high spatio-temporal resolution modeling is performed for a small and well-equipped urban catchment. The aim of this work is to identify urban modeling needs in terms of spatial and temporal resolution especially for a very small urban area (3.7 ha urban catchment located in the Perreux-sur-Marne city at the southeast of Paris) MultiHydro model was selected to carry out this work, it is a physical based and fully distributed model that interacts four existing modules each of them representing a portion of the water cycle in urban environments. MultiHydro was implemented at 10m, 5m and 2m resolution. Simulations were performed at different spatio-temporal resolutions and analyzed with respect to real flow measurements. First Results coming out show improvements obtained in terms of the model performance at high spatio-temporal resolution.

Simulating the production and dispersion of environmental pollutants in aerosol phase in an urban area of great historical and cultural value.

PubMed

Librando, Vito; Tringali, Giuseppe; Calastrini, Francesca; Gualtieri, Giovanni

2009-11-01

Mathematical models were developed to simulate the production and dispersion of aerosol phase atmospheric pollutants which are the main cause of the deterioration of monuments of great historical and cultural value. This work focuses on Particulate Matter (PM) considered the primary cause of monument darkening. Road traffic is the greatest contributor to PM in urban areas. Specific emission and dispersion models were used to study typical urban configurations. The area selected for this study was the city of Florence, a suitable test bench considering the magnitude of architectural heritage together with the remarkable effect of the PM pollution from road traffic. The COPERT model, to calculate emissions, and the street canyon model coupled with the CALINE model, to simulate pollutant dispersion, were used. The PM concentrations estimated by the models were compared to actual PM concentration measurements, as well as related to the trend of some meteorological variables. The results obtained may be defined as very encouraging even the models correlated poorly: the estimated concentration trends as daily averages moderately reproduce the same trends of the measured values.

Remote Sensing and Spatial Growth Modeling Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Khan, Maudood

2006-01-01

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 80 percent of the world s population will live in cities. Directly aligned with the expansion of cities is urban sprawl. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes. A reduction in air quality over cities is a major result of these impacts. Strategies that can be directly or indirectly implemented to help remediate air quality problems in cities and that can be accepted by political decision makers and the general public are now being explored to help bring down air pollutants and improve air quality. The urban landscape is inherently complex and this complexity is not adequately captured in air quality models, particularly the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to the meteorology component of the CMAQ model focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how ozone and air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rationale decisions on urban growth and sustainability for the metropolitan area in the future.

Development of a Green Roof Environmental Monitoring and Meteorological Network in New York City

PubMed Central

Gaffin, Stuart R.; Khanbilvardi, Reza; Rosenzweig, Cynthia

2009-01-01

Green roofs (with plant cover) are gaining attention in the United States as a versatile new environmental mitigation technology. Interest in data on the environmental performance of these systems is growing, particularly with respect to urban heat island mitigation and stormwater runoff control. We are deploying research stations on a diverse array of green roofs within the New York City area, affording a new opportunity to monitor urban environmental conditions at small scales. We show some green roof systems being monitored, describe the sensor selection employed to study energy balance, and show samples of selected data. These roofs should be superior to other urban rooftops as sites for meteorological stations. PMID:22574037

Development of a green roof environmental monitoring and meteorological network in new york city.

PubMed

Gaffin, Stuart R; Khanbilvardi, Reza; Rosenzweig, Cynthia

2009-01-01

Green roofs (with plant cover) are gaining attention in the United States as a versatile new environmental mitigation technology. Interest in data on the environmental performance of these systems is growing, particularly with respect to urban heat island mitigation and stormwater runoff control. We are deploying research stations on a diverse array of green roofs within the New York City area, affording a new opportunity to monitor urban environmental conditions at small scales. We show some green roof systems being monitored, describe the sensor selection employed to study energy balance, and show samples of selected data. These roofs should be superior to other urban rooftops as sites for meteorological stations.

Assessment and prediction of short term hospital admissions: the case of Athens, Greece

NASA Astrophysics Data System (ADS)

Kassomenos, P.; Papaloukas, C.; Petrakis, M.; Karakitsios, S.

The contribution of air pollution on hospital admissions due to respiratory and heart diseases is a major issue in the health-environmental perspective. In the present study, an attempt was made to run down the relationships between air pollution levels and meteorological indexes, and corresponding hospital admissions in Athens, Greece. The available data referred to a period of eight years (1992-2000) including the daily number of hospital admissions due to respiratory and heart diseases, hourly mean concentrations of CO, NO 2, SO 2, O 3 and particulates in several monitoring stations, as well as, meteorological data (temperature, relative humidity, wind speed/direction). The relations among the above data were studied through widely used statistical techniques (multivariate stepwise analyses) and Artificial Neural Networks (ANNs). Both techniques revealed that elevated particulate concentrations are the dominant parameter related to hospital admissions (an increase of 10 μg m -3 leads to an increase of 10.2% in the number of admissions), followed by O 3 and the rest of the pollutants (CO, NO 2 and SO 2). Meteorological parameters also play a decisive role in the formation of air pollutant levels affecting public health. Consequently, increased/decreased daily hospital admissions are related to specific types of meteorological conditions that favor/do not favor the accumulation of pollutants in an urban complex. In general, the role of meteorological factors seems to be underestimated by stepwise analyses, while ANNs attribute to them a more important role. Comparison of the two models revealed that ANN adaptation in complicate environmental issues presents improved modeling results compared to a regression technique. Furthermore, the ANN technique provides a reliable model for the prediction of the daily hospital admissions based on air quality data and meteorological indices, undoubtedly useful for regulatory purposes.

The COCCON Paris Experiment - Model-Data Comparison of XCO2 (and XCH4) in an Urban Environment

NASA Astrophysics Data System (ADS)

Vogel, F. R.; Staufer, J.; Frey, M.; Broquet, G.; Xueref-Remy, I.; Sha, M. K.; Blumenstock, T.; Te, Y. V.; Janssen, C.; Jeseck, P.; Chelin, P.; Fratacci, T.; Tu, Q.; Gross, J.; Schäfer, K.; Orphal, J.; Ciais, P.; Hase, F.

2016-12-01

Currently, over 50% of the global population lives in urban areas1 and the future population growth is also predicted to occur mostly in urban centers. While emissions of Greenhouse Gases and carbon-based air pollutants can be estimated quite precisely on national scale using fuel consumption statistics, typically to about 3%-40%2, higher uncertainties of 20%-50% are reported3 for urban GHG emissions. Atmospheric observations, when combined with inversion modelling can allow independently assessing such urban emission inventories4. This study investigates how well novel low-resolution FTS observations can be represented within atmospheric transport models used in such inversion systems, which would be the pre-requisite for a future system based on XCO2 observations. A network of five EM27sun instruments5,6was deployed across the Paris Metropolitan region (upwind, downwind and inside of Paris, diameter ca. 40km) for a three week period in spring 2015. Observed XCO2 significantly varies during this period ranging from 400.5ppm to 406ppm. A decrease in XCO2 throughout the day, likely driven by the biogenic CO2 uptake in the region, is recorded at all sites. Both observational and simulated XCO2 also clearly show that the emissions in the Paris region significantly increase XCO2 (0-2ppm), depending on meteorological conditions. The observational data is compared to three configurations of our XCO2 forward model to assess their performance. We find that all simulations and observations agree qualitatively and that the gradient of XCO2 over Paris can also be reproduced quantitatively for specific meteorological conditions and optimal model setup. 1United Nations, Department of Economic and Social Affairs, Population Division (2014). World Urbanization Prospects: The 2014 Revision 2Anders et al. 2014, Tellus B 2014, 66, 23616, http://dx.doi.org/10.3402/tellusb.v66.23616 3Wu et al. 2016, Atmos. Chem. Phys., 16, 7743-7771, doi:10.5194/acp-16-7743-2016 4Staufer et al. 2016, Atmos. Chem. Phys. Diss., under review for ACP, doi:10.5194/acp-2016-191 5Gisi et al., Atmos. Meas. Tech., 5, 2969-2980, doi:10.5194/amt-5-2969-2012, 2012 6Hase et al. 2015, Atmos. Meas. Tech., 8, 3047-3057, doi :10.5194/amt-8-3047-2015

Assessing measurement uncertainty in meteorology in urban environments

NASA Astrophysics Data System (ADS)

Curci, S.; Lavecchia, C.; Frustaci, G.; Paolini, R.; Pilati, S.; Paganelli, C.

2017-10-01

Measurement uncertainty in meteorology has been addressed in a number of recent projects. In urban environments, uncertainty is also affected by local effects which are more difficult to deal with than for synoptic stations. In Italy, beginning in 2010, an urban meteorological network (Climate Network®) was designed, set up and managed at national level according to high metrological standards and homogeneity criteria to support energy applications. The availability of such a high-quality operative automatic weather station network represents an opportunity to investigate the effects of station siting and sensor exposure and to estimate the related measurement uncertainty. An extended metadata set was established for the stations in Milan, including siting and exposure details. Statistical analysis on an almost 3-year-long operational period assessed network homogeneity, quality and reliability. Deviations from reference mean values were then evaluated in selected low-gradient local weather situations in order to investigate siting and exposure effects. In this paper the methodology is depicted and preliminary results of its application to air temperature discussed; this allowed the setting of an upper limit of 1 °C for the added measurement uncertainty at the top of the urban canopy layer.

Comparison of Wind Speeds and Temperatures Simulated by the Local Data Assimilation and Prediction System with Those observed at AWSs in Korea

NASA Astrophysics Data System (ADS)

KIM, D. J.; Kim, J.

2017-12-01

In this study, the characteristics of 10-m wind speeds and 2-m temperatures predicted by the local data assimilation and prediction system (LDAPS) in Korea meteorological administration (KMA) were analyzed by comparing those observed at automatic weather stations (AWSs). The LDAPS is a currently operating meteorology prediction system with the horizontal resolution of about 1.5 km. We classified the AWSs into four categories (urban, rural, coastal, and mountainous areas) based on the surrounding land-use types and locations of the AWSs and selected 30 AWSs for each category. For each category, we investigated how well the LDAPS predicted 10-m wind speeds and 2-m temperatures at the AWSs and statistically analyzed the LDAPS characteristics in predicting the meteorological variables. In the mountainous area, the LDAPS underestimated 2-m temperatures due to the resolution and coordinate system of the LDAPS. In the urban area, the LDAPS overestimated the 10-m wind speeds and underestimated the 2-m temperatures, implying that the LDAPS should consider the physical process to reflect the urban effects on wind speeds and temperatures in urban areas.

Seasonal variation of Ganoderma spore concentrations in urban and suburban districts of the city of Szczecin, Poland.

PubMed

Grinn-Gofroń, Agnieszka; Strzelczak, Agnieszka; Przestrzelska, Katarzyna

2015-01-01

According to recent studies, Ganoderma may be the third genus, after Alternaria and Cladosporium, the spores of which cause symptoms of allergy, and concentration is related to meteorological factors. The aerobiology of Ganoderma spores in Szczecin in urban and suburban districts was examined using Lanzoni Volumetric Spore Traps in 2008-2010. Ganoderma spores were present in the atmosphere on more than 90% of the days from June through September with peak concentrations in June, July and September. The number of days with spores was lower in the suburban district, while the total number of spores collected was higher there than in the urban district. Correlation and multiple regression analyses revealed weak relationships between Ganoderma and meteorological conditions, while testing the significance of differences between the districts showed that urban development did not have a clear impact on the values of meteorological parameters. A significantly higher abundance of spores in the suburbs of Szczecin seemed to be conditioned by the closeness of potential area sources. This study indicates that a single measuring site in the city centre insufficiently reflected the dynamics and level of Ganoderma spore concentration in peripheral districts.

Observing the Vertical Dimensions of Singapore's Urban Heat Island

NASA Astrophysics Data System (ADS)

Chow, W. T. L.; Ho, D. X. Q.

2015-12-01

In numerous cities, measurements of urban warmth in most urban heat island (UHI) studies are generally constrained towards surface or near-surface (<2 m above ground) levels across horizontal variations in land use and land cover. However, there has been hitherto limited attention towards the measurement of vertical temperature profiles extending from the urban surface through to the urban boundary layer. Knowledge of these profiles, through how they vary over different local urban morphologies, and develop with respect to synoptic meteorological conditions, are important towards several aspects of UHI research; these include validating modelling urban canopy lapse rate profiles or estimating the growth of urban plumes. In this study, we utilised temperature sensors attached onto remote controlled aerial quadcopter platforms to measure urban temperature and humidity profiles in Singapore, which is a rapidly urbanizing major tropical metropolis. These profiles were measured from the surface to ~100 m above ground level, a height which includes all of the urban canopy and parts of the urban boundary layer. Initial results indicate significant variations in stability measured over different land uses (e.g. urban park, high-rise residential, commercial); these profiles are also temporally dynamic, depending on the time of day and larger-scale weather conditions.

Effects of canyon geometry on the distribution of traffic-related air pollution in a large urban area: Implications of a multi-canyon air pollution dispersion model

NASA Astrophysics Data System (ADS)

Fu, Xiangwen; Liu, Junfeng; Ban-Weiss, George A.; Zhang, Jiachen; Huang, Xin; Ouyang, Bin; Popoola, Olalekan; Tao, Shu

2017-09-01

Street canyons are ubiquitous in urban areas. Traffic-related air pollutants in street canyons can adversely affect human health. In this study, an urban-scale traffic pollution dispersion model is developed considering street distribution, canyon geometry, background meteorology, traffic assignment, traffic emissions and air pollutant dispersion. In the model, vehicle exhausts generated from traffic flows first disperse inside street canyons along the micro-scale wind field generated by computational fluid dynamics (CFD) model. Then, pollutants leave the street canyon and further disperse over the urban area. On the basis of this model, the effects of canyon geometry on the distribution of NOx and CO from traffic emissions were studied over the center of Beijing. We found that an increase in building height leads to heavier pollution inside canyons and lower pollution outside canyons at pedestrian level, resulting in higher domain-averaged concentrations over the area. In addition, canyons with highly even or highly uneven building heights on each side of the street tend to lower the urban-scale air pollution concentrations at pedestrian level. Further, increasing street widths tends to lead to lower pollutant concentrations by reducing emissions and enhancing ventilation simultaneously. Our results indicate that canyon geometry strongly influences human exposure to traffic pollutants in the populated urban area. Carefully planning street layout and canyon geometry while considering traffic demand as well as local weather patterns may significantly reduce inhalation of unhealthy air by urban residents.

Assessing summertime urban air conditioning consumption in a semiarid environment

NASA Astrophysics Data System (ADS)

Salamanca, F.; Georgescu, M.; Mahalov, A.; Moustaoui, M.; Wang, M.; Svoma, B. M.

2013-09-01

Evaluation of built environment energy demand is necessary in light of global projections of urban expansion. Of particular concern are rapidly expanding urban areas in environments where consumption requirements for cooling are excessive. Here, we simulate urban air conditioning (AC) electric consumption for several extreme heat events during summertime over a semiarid metropolitan area with the Weather Research and Forecasting (WRF) model coupled to a multilayer building energy scheme. Observed total load values obtained from an electric utility company were split into two parts, one linked to meteorology (i.e., AC consumption) which was compared to WRF simulations, and another to human behavior. WRF-simulated non-dimensional AC consumption profiles compared favorably to diurnal observations in terms of both amplitude and timing. The hourly ratio of AC to total electricity consumption accounted for ˜53% of diurnally averaged total electric demand, ranging from ˜35% during early morning to ˜65% during evening hours. Our work highlights the importance of modeling AC electricity consumption and its role for the sustainable planning of future urban energy needs. Finally, the methodology presented in this article establishes a new energy consumption-modeling framework that can be applied to any urban environment where the use of AC systems is prevalent.

A study of model parameters associated with the urban climate using HCMM data

NASA Technical Reports Server (NTRS)

1981-01-01

Infrared and visible data from the Heat Capacity Mapping Mission (HCMM) satellite were used to study the intensity of the urban heat island, commonly defined as the temperature difference between the center of the city and the surrounding suburban and rural regions, as a function of changes in the season and changes in meteorological conditions in order to derive various parameters which may be used in numerical models for urban climate. The analysis was focused on the city of St. Louis; and in situ data from St. Louis was combined with HCMM data in order to derive the various parameters. The HCMM data were mapped onto a Mercator projection map of the city and ground temperatures were established using data corrected for the effects of atmospheric absorption. The corrected and uncorrected HCMM data were compared to determine the magnitude of the error induced by atmospheric effects.

Overview of the Brooklyn traffic real-time ambient pollutant penetration and environmental dispersion (B-TRAPPED) study: theoretical background and model for design of field experiments.

PubMed

Hahn, Intaek; Wiener, Russell W; Richmond-Bryant, Jennifer; Brixey, Laurie A; Henkle, Stacy W

2009-12-01

The Brooklyn traffic real-time ambient pollutant penetration and environmental dispersion (B-TRAPPED) study was a multidisciplinary field research project that investigated the transport, dispersion, and infiltration processes of traffic emission particulate matter (PM) pollutants in a near-highway urban residential area. The urban PM transport, dispersion, and infiltration processes were described mathematically in a theoretical model that was constructed to develop the experimental objectives of the B-TRAPPED study. In the study, simultaneous and continuous time-series PM concentration and meteorological data collected at multiple outdoor and indoor monitoring locations were used to characterize both temporal and spatial patterns of the PM concentration movements within microscale distances (<500 m) from the highway. Objectives of the study included (1) characterizing the temporal and spatial PM concentration fluctuation and distribution patterns in the urban street canyon; (2) investigating the effects of urban structures such as a tall building or an intersection on the transport and dispersion of PM; (3) studying the influence of meteorological variables on the transport, dispersion, and infiltration processes; (4) characterizing the relationships between the building parameters and the infiltration mechanisms; (5) establishing a cause-and-effect relationship between outdoor-released PM and indoor PM concentrations and identifying the dominant mechanisms involved in the infiltration process; (6) evaluating the effectiveness of a shelter-in-place area for protection against outdoor-released PM pollutants; and (7) understanding the predominant airflow and pollutant dispersion patterns within the neighborhood using wind tunnel and CFD simulations. The 10 papers in this first set of papers presenting the results from the B-TRAPPED study address these objectives. This paper describes the theoretical background and models representing the interrelated processes of transport, dispersion, and infiltration. The theoretical solution for the relationship between the time-dependent indoor PM concentration and the initial PM concentration at the outdoor source was obtained. The theoretical models and solutions helped us to identify important parameters in the processes of transport, dispersion, and infiltration. The B-TRAPPED study field experiments were then designed to investigate these parameters in the hope of better understanding urban PM pollutant behaviors.

High-resolution spatial distribution of temperature over Berlin simulated by the mesoscale model METRAS and comparison with measured data

NASA Astrophysics Data System (ADS)

Sodoudi, Sahar; Schäfer, Kerstin; Grawe, David; Petrik, Ronny; Heinke Schlünzen, K.

2014-05-01

The world's population is projected to increase in the next decades especially in urban areas. Additionally, the living conditions are affected largely by the local urban climate. The urban climate is a complex local system which might change differently than the regional climate. Studying the spatial distribution of air temperature and urban heat island intensity is one of the major concerns in the climate change scenarios. Due to the expected higher frequency of heat waves in the future and the related heat stress, high resolution distribution of air temperature is an important key for urban planning and development. In this study the non-hydrostatic Mesoscale Transport and Fluid Model (METRAS) developed at the University of Hamburg is used to simulate the air temperature for the urban area of Berlin. The forcing data have been derived from the ECMWF reanalysis data. We have used three nested domains (resolution of 4 km, 1 km, 200 m) to simulate the temperature in Berlin. Evaluation of these mesoscale model results is challenging for urban areas, due to the sparse and heterogeneous distribution of meteorological stations and the heterogeneous land cover in urban areas. The Meteorological Institute of the Free University of Berlin organized six measurement campaigns in 2012. Measurements were taken at 31 different routes through Berlin using mobile measurement systems. In comparison with data from permanent weather stations the mobile measurements show a general overestimation of temperature and underestimation of relative humidity values. This may be the result of the different land cover types and places, where the mobile measurements and the stationary measurements were taken. The highly resolved (200 m) simulated air temperature from METRAS has been verified for three different selected summer days in 2012 with different pressure patterns over Berlin. For the model evaluation, the data from the measuring campaign and 34 permanent stations have been used. The results show that METRAS overestimated the cloud water and rain water content on the first two selected days. The air temperature on the first two days has been underestimated by the model due to the reduced incoming radiation, and the strength of the urban heat island has not been reproduced. The mean absolute error is higher during the day time and especially in the city center. The last selected day is a sunny day with light wind from the Northwest. On this day the diurnal temperature variation is well reproduced by the model, although METRAS predicts short showers for several small areas during the afternoon. The showers do not lead to a temperature decrease over the whole city. The mean absolute error is much smaller in comparison with the other days. The temperature peak and the urban heat island are well consistent with observations. The mean absolute error is smaller in the city center and larger over the green areas. The spatial distribution of simulated temperature is in a good agreement with the measurements.

Sensitivity study of the UHI in the city of Szeged (Hungary) to different offline simulation set-ups using SURFEX/TEB

NASA Astrophysics Data System (ADS)

Zsebeházi, Gabriella; Hamdi, Rafiq; Szépszó, Gabriella

2015-04-01

Urbanised areas modify the local climate due to the physical properties of surface subjects and their morphology. The urban effect on local climate and regional climate change interact, resulting in more serious climate change impacts (e.g., more heatwave events) over cities. Majority of people are now living in cities and thus, affected by these enhanced changes. Therefore, targeted adaptation and mitigation strategies in cities are of high importance. Regional climate models (RCMs) are sufficient tools for estimating future climate change of an area in detail, although most of them cannot represent the urban climate characteristics, because their spatial resolution is too coarse (in general 10-50 km) and they do not use a specific urban parametrization over urbanized areas. To describe the interactions between the urban surface and atmosphere on few km spatial scale, we use the externalised SURFEX land surface scheme including the TEB urban canopy model in offline mode (i.e. the interaction is only one-way). The driving atmospheric conditions highly influence the impact results, thus the good quality of these data is particularly essential. The overall aim of our research is to understand the behaviour of the impact model and its interaction with the forcing coming from the atmospheric model in order to reduce the biases, which can lead to qualified impact studies of climate change over urban areas. As a preliminary test, several short (few-day) 1 km resolution simulations are carried out over a domain covering a Hungarian town, Szeged, which is located at the flat southern part of Hungary. The atmospheric forcing is provided by ALARO (a new version of the limited-area model of the ARPEGE-IFS system running at the Royal Meteorological Institute of Belgium) applied over Hungary. The focal point of our investigations is the ability of SURFEX to simulate the diurnal evolution and spatial pattern of urban heat island (UHI). Different offline simulation set-ups have been tested: 1. Atmospheric forcing at 4km and 10km resolutions; 2. Atmospheric forcing prepared with and without TEB; 3. Coupling of forcings on 3h and 1h temporal frequencies; 4. Different forcing levels on 50m, 40m, 30m, 20m, 10m; 5. Different computation method of 2m temperature using CANOPY, Paulson, and Geleyn schemes. Finally, some outcomes are also compared to the results obtained using ALADIN-Climate RCM (adapted and used at the Hungarian Meteorological Service on 10 km resolution) as driving atmospheric model. The presentation is dedicated to show the results and main conclusions of our studies.

Evaluation of urban surface parameterizations in the WRF model using measurements during the Texas Air Quality Study 2006 field campaign

NASA Astrophysics Data System (ADS)

Lee, S.-H.; Kim, S.-W.; Angevine, W. M.; Bianco, L.; McKeen, S. A.; Senff, C. J.; Trainer, M.; Tucker, S. C.; Zamora, R. J.

2011-03-01

The performance of different urban surface parameterizations in the WRF (Weather Research and Forecasting) in simulating urban boundary layer (UBL) was investigated using extensive measurements during the Texas Air Quality Study 2006 field campaign. The extensive field measurements collected on surface (meteorological, wind profiler, energy balance flux) sites, a research aircraft, and a research vessel characterized 3-dimensional atmospheric boundary layer structures over the Houston-Galveston Bay area, providing a unique opportunity for the evaluation of the physical parameterizations. The model simulations were performed over the Houston metropolitan area for a summertime period (12-17 August) using a bulk urban parameterization in the Noah land surface model (original LSM), a modified LSM, and a single-layer urban canopy model (UCM). The UCM simulation compared quite well with the observations over the Houston urban areas, reducing the systematic model biases in the original LSM simulation by 1-2 °C in near-surface air temperature and by 200-400 m in UBL height, on average. A more realistic turbulent (sensible and latent heat) energy partitioning contributed to the improvements in the UCM simulation. The original LSM significantly overestimated the sensible heat flux (~200 W m-2) over the urban areas, resulting in warmer and higher UBL. The modified LSM slightly reduced warm and high biases in near-surface air temperature (0.5-1 °C) and UBL height (~100 m) as a result of the effects of urban vegetation. The relatively strong thermal contrast between the Houston area and the water bodies (Galveston Bay and the Gulf of Mexico) in the LSM simulations enhanced the sea/bay breezes, but the model performance in predicting local wind fields was similar among the simulations in terms of statistical evaluations. These results suggest that a proper surface representation (e.g. urban vegetation, surface morphology) and explicit parameterizations of urban physical processes are required for accurate urban atmospheric numerical modeling.

Assessment of impact of unaccounted emission on ambient concentration using DEHM and AERMOD in combination with WRF

NASA Astrophysics Data System (ADS)

Kumar, Awkash; Patil, Rashmi S.; Dikshit, Anil Kumar; Kumar, Rakesh; Brandt, Jørgen; Hertel, Ole

2016-10-01

The accuracy of the results from an air quality model is governed by the quality of emission and meteorological data inputs in most of the cases. In the present study, two air quality models were applied for inverse modelling to determine the particulate matter emission strengths of urban and regional sources in and around Mumbai in India. The study takes outset in an existing emission inventory for Total Suspended Particulate Matter (TSPM). Since it is known that the available TSPM inventory is uncertain and incomplete, this study will aim for qualifying this inventory through an inverse modelling exercise. For use as input to the air quality models in this study, onsite meteorological data has been generated using the Weather Research Forecasting (WRF) model. The regional background concentration from regional sources is transported in the atmosphere from outside of the study domain. The regional background concentrations of particulate matter were obtained from model calculations with the Danish Eulerian Hemisphere Model (DEHM) for regional sources. The regional background concentrations obtained from DEHM were then used as boundary concentrations in AERMOD calculations of the contribution from local urban sources. The results from the AERMOD calculations were subsequently compared with observed concentrations and emission correction factors obtained by best fit of the model results to the observed concentrations. The study showed that emissions had to be up-scaled by between 14 and 55% in order to fit the observed concentrations; this is of course when assuming that the DEHM model describes the background concentration level of the right magnitude.

Development of a multi-sensor based urban discharge forecasting system using remotely sensed data: A case study of extreme rainfall in South Korea

NASA Astrophysics Data System (ADS)

Yoon, Sunkwon; Jang, Sangmin; Park, Kyungwon

2017-04-01

Extreme weather due to changing climate is a main source of water-related disasters such as flooding and inundation and its damage will be accelerated somewhere in world wide. To prevent the water-related disasters and mitigate their damage in urban areas in future, we developed a multi-sensor based real-time discharge forecasting system using remotely sensed data such as radar and satellite. We used Communication, Ocean and Meteorological Satellite (COMS) and Korea Meteorological Agency (KMA) weather radar for quantitative precipitation estimation. The Automatic Weather System (AWS) and McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation (MAPLE) were used for verification of rainfall accuracy. The optimal Z-R relation was applied the Tropical Z-R relationship (Z=32R1.65), it has been confirmed that the accuracy is improved in the extreme rainfall events. In addition, the performance of blended multi-sensor combining rainfall was improved in 60mm/h rainfall and more strong heavy rainfall events. Moreover, we adjusted to forecast the urban discharge using Storm Water Management Model (SWMM). Several statistical methods have been used for assessment of model simulation between observed and simulated discharge. In terms of the correlation coefficient and r-squared discharge between observed and forecasted were highly correlated. Based on this study, we captured a possibility of real-time urban discharge forecasting system using remotely sensed data and its utilization for real-time flood warning. Acknowledgement This research was supported by a grant (13AWMP-B066744-01) from Advanced Water Management Research Program (AWMP) funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korean government.

Meteorological and chemical impacts on ozone formation: A case study in Hangzhou, China

NASA Astrophysics Data System (ADS)

Li, Kangwei; Chen, Linghong; Ying, Fang; White, Stephen J.; Jang, Carey; Wu, Xuecheng; Gao, Xiang; Hong, Shengmao; Shen, Jiandong; Azzi, Merched; Cen, Kefa

2017-11-01

Regional ozone pollution has become one of the most challenging problems in China, especially in the more economically developed and densely populated regions like Hangzhou. In this study, measurements of O3, CO, NOx and non-methane hydrocarbons (NMHCs), together with meteorological data, were obtained for the period July 1, 2013-August 15, 2013 at three sites in Hangzhou. These sites included an urban site (Zhaohui ;ZH;), a suburban site (Xiasha ;XS;) and a rural site (Qiandaohu ;QDH;). During the observation period, both ZH and XS had a higher ozone level than QDH, with exceeding rates of 41.3% and 47.8%, respectively. Elevated O3 levels in QDH were found at night, which could be explained by less prominent NO titration effect in rural area. Detailed statistical analysis of meteorological and chemical impacts on ozone formation was carried out for ZH, and higher ozone concentration was observed when the wind direction was from the east. This is possibly due to emissions of VOCs from XS, a typical chemical industrial park located in 30 km upwind area of ZH. A comprehensive comparison between three ozone episode periods and one non-episode period were made in ZH. It was concluded that elevated concentrations of precursors and temperatures, low relative humidity and wind speed and easterly-dominated wind direction contribute to urban ozone episodes in Hangzhou. VOCs reactivity analysis indicated that reactive alkenes like isoprene and isobutene contributed most to ozone formation. Three methods were applied to evaluate O3-VOCs-NOx sensitivity in ZH: VOCs/NOx ratio method, Smog Production Model (SPM) and Relative Incremental Reactivity (RIR). The results show that summer ozone in urban Hangzhou mostly presents VOCs-limited and transition region alternately. Our study implies that the increasing automobiles and VOCs emissions from upwind area could result in ozone pollution in urban Hangzhou, and synergistic reduction of VOCs and NOx will be more effective.

The urban boundary-layer field campaign in marseille (ubl/clu-escompte): set-up and first results

NASA Astrophysics Data System (ADS)

Mestayer, P.G.; Durand, P.; Augustin, P.; Bastin, S.; Bonnefond, J.-M.; Benech, B.; Campistron, B.; Coppalle, A.; Delbarre, H.; Dousset, B.; Drobinski, P.; Druilhet, A.; Frejafon, E.; Grimmond, C.S.B.; Groleau, D.; Irvine, M.; Kergomard, C.; Kermadi, S.; Lagouarde, J.-P.; Lemonsu, A.; Lohou, F.; Long, N.; Masson, V.; Moppert, C.; Noilhan, J.; Offerle, B.; Oke, T.R.; Pigeon, G.; Puygrenier, V.; Roberts, S.; Rosant, J.-M.; Sanid, F.; Salmond, J.; Talbaut, M.; Voogt, J.

The UBL/CLU (urban boundary layer/couche limite urbaine) observation and modelling campaign is a side-project of the regional photochemistry campaign ESCOMPTE. UBL/CLU focuses on the dynamics and thermodynamics of the urban boundary layer of Marseille, on the Mediterranean coast of France. The objective of UBL/CLU is to document the four-dimensional structure of the urban boundary layer and its relation to the heat and moisture exchanges between the urban canopy and the atmosphere during periods of low wind conditions, from June 4 to July 16, 2001. The project took advantage of the comprehensive observational set-up of the ESCOMPTE campaign over the Berre-Marseille area, especially the ground-based remote sensing, airborne measurements, and the intensive documentation of the regional meteorology. Additional instrumentation was installed as part of UBL/CLU. Analysis objectives focus on (i) validation of several energy balance computational schemes such as LUMPS, TEB and SM2-U, (ii) ground truth and urban canopy signatures suitable for the estimation of urban albedos and aerodynamic surface temperatures from satellite data, (iii) high resolution mapping of urban land cover, land-use and aerodynamic parameters used in UBL models, and (iv) testing the ability of high resolution atmospheric models to simulate the structure of the UBL during land and sea breezes, and the related transport and diffusion of pollutants over different districts of the city. This paper presents initial results from such analyses and details of the overall experimental set-up.

THE MADISON SQUARE GARDEN DISPERSION STUDY (MSG05) METEOROLOGICAL DATA DESCRIPTION.

DOE Office of Scientific and Technical Information (OSTI.GOV)

REYNOLDS, R.M.

2006-10-01

MSG05 was a study of atmospheric transport and dispersion in the deep urban canyons of Midtown New York City, in the area of Madison Square Garden. This downtown area is considered to be a prime target for terrorist activities, and has one of the largest commuter populations in the world. Little is known about air flow and hazardous gas dispersion in such scenarios, since previous urban field experiments have focused on small to medium sized cities with much smaller street canyons. On March 10 and 14, 2005, a series of Perfluorocarbon Tracer (PFT) tracers were released and tracked with aboutmore » 30 sampling stations at radial distances of about 0.2 and 0.4 km, with vertical profiles near a 250 m tall building (One Penn Plaza). Meteorological stations collected wind data in the MSG vicinity, at street level and rooftop level. MSG05 is expected to provide useful information on rapid vertical dispersion will assist in planning for more extensive studies. This data release is being made available to a restricted group of key scientists who have worked on the project. Part of the QA program involves feedback from scientists and modelers who are working on this study. This document describes the meteorological component of the project. The file organization and metadata are detailed so that a researcher can work with the data sets.« less

Impact of two chemistry mechanisms fully coupled with mesoscale model on the atmospheric pollutants distribution

NASA Astrophysics Data System (ADS)

Arteta, J.; Cautenet, S.; Taghavi, M.; Audiffren, N.

Air quality models (AQM) consist of many modules (meteorology, emission, chemistry, deposition), and in some conditions such as: vicinity of clouds or aerosols plumes, complex local circulations (mountains, sea breezes), fully coupled models (online method) are necessary. In order to study the impact of lumped chemical mechanisms in AQM simulations, we examine the ability of both different chemical mechanisms: (i) simplified: Condensed Version of the MOdèle de Chimie Atmosphérique 2.2 (CV-MOCA2.2), and (ii) reference: Regional Atmospheric Chemistry Model (RACM), which are coupled online with the Regional Atmospheric Modeling Systems (RAMS) model, on the distribution of pollutants. During the ESCOMPTE experiment (Expérience sur Site pour COntraindre les Modèles de Pollution et de Transport d'Emissions) conducted over Southern France (including urban and industrial zones), Intensive observation periods (IOP) characterized by various meteorological and mixed chemical conditions are simulated. For both configurations of modeling, numerical results are compared with surface measurements (75 stations) for primary (NO x) and secondary (O 3) species. We point out the impact of the two different chemical mechanisms on the production of species involved in the oxidizing capacity such as ozone and radicals within urban and industrial areas. We highlight that both chemical mechanisms produce very similar results for the main pollutants (NO x and O 3) in three-dimensional (3D) distribution, despite large discrepancies in 0D modeling. For ozone concentration, we found sometimes small differences (5-10 ppb) between the mechanisms under study according to the cases (polluted or not). The relative difference between the two mechanisms over the whole domain is only -7% for ozone from CV-MOCA 2.2 versus RACM. When the order of magnitude is needed rather than an accurate estimate, a reduced mechanism is satisfactory. It has the advantage of running faster (four times less than CPU time on SGI 3800 with 30 processors). Simplified mechanisms are really important to study cases for which an online coupling is necessary between meso-scale and chemistry models (clouds or aerosols plumes impacts, highly variable meteorology).

Urban compaction or dispersion? An air quality modelling study

NASA Astrophysics Data System (ADS)

Martins, Helena

2012-07-01

Urban sprawl is altering the landscape, with current trends pointing to further changes in land use that will, in turn, lead to changes in population, energy consumption, atmospheric emissions and air quality. Urban planners have debated on the most sustainable urban structure, with arguments in favour and against urban compaction and dispersion. However, it is clear that other areas of expertise have to be involved. Urban air quality and human exposure to atmospheric pollutants as indicators of urban sustainability can contribute to the discussion, namely through the study of the relation between urban structure and air quality. This paper addresses the issue by analysing the impacts of alternative urban growth patterns on the air quality of Porto urban region in Portugal, through a 1-year simulation with the MM5-CAMx modelling system. This region has been experiencing one of the highest European rates of urban sprawl, and at the same time presents a poor air quality. As part of the modelling system setup, a sensitivity study was conducted regarding different land use datasets and spatial distribution of emissions. Two urban development scenarios were defined, SPRAWL and COMPACT, together with their new land use and emission datasets; then meteorological and air quality simulations were performed. Results reveal that SPRAWL land use changes resulted in an average temperature increase of 0.4 °C, with local increases reaching as high as 1.5 °C. SPRAWL results also show an aggravation of PM10 annual average values and an increase in the exceedances to the daily limit value. For ozone, differences between scenarios were smaller, with SPRAWL presenting larger concentration differences than COMPACT. Finally, despite the higher concentrations found in SPRAWL, population exposure to the pollutants is higher for COMPACT because more inhabitants are found in areas of highest concentration levels.

Assessing the effect of wind speed/direction changes on urban heat island intensity of Istanbul.

NASA Astrophysics Data System (ADS)

Perim Temizoz, Huriye; Unal, Yurdanur S.

2017-04-01

Assessing the effect of wind speed/direction changes on urban heat island intensity of Istanbul. Perim Temizöz, Deniz H. Diren, Cemre Yürük and Yurdanur S. Ünal Istanbul Technical University, Department of Meteorological Engineering, Maslak, Istanbul, Turkey City or metropolitan areas are significantly warmer than the outlying rural areas since the urban fabrics and artificial surfaces which have different radiative, thermal and aerodynamic features alter the surface energy balance, interact with the regional circulation and introduce anthropogenic sensible heat and moisture into the atmosphere. The temperature contrast between urban and rural areas is most prominent during nighttime since heat is absorbed by day and emitted by night. The intensity of the urban heat island (UHI) vary considerably depending on the prevailent meteorological conditions and the characteristics of the region. Even though urban areas cover a small fraction of Earth, their climate has greater impact on the world's population. Over half of the world population lives in the cities and it is expected to rise within the coming decades. Today almost one fifth of the Turkey's population resides in Istanbul with the percentage expected to increase due to the greater job opportunities compared to the other cities. Its population has been increased from 2 millions to 14 millions since 1960s. Eventually, the city has been expanded tremendously within the last half century, shifting the landscape from vegetation to built up areas. The observations of the last fifty years over Istanbul show that the UHI is most pronounced during summer season. The seasonal temperature differences between urban and suburban sites reach up to 3 K and roughly haft degree increase in UHI intensity is observed after 2000. In this study, we explore the possible range of heat load and distribution over Istanbul for different prevailing wind conditions by using the non-hydrostatic MUKLIMO3 model developed by DWD (Deutscher Wetterdienst). The study is focused on the spatial gradients of temperature, humidity and winds during summer. The model run by the average temperature and humidity vertical profiles over Istanbul during summer season with 200 m resolution. A series of sensitivity tests are carried out for different wind speeds (1-5 m/sec) and prevailing wind directions. Land use data are created by combining the geographical data obtained from Istanbul Metropolitan Municipality and CORINE Land Cover Raster Data. The land use table involves 25 land use types. The residential areas are classified considering the percentage of the building coverages and the average height of the buildings within the grid cell. The associated parameters in land use table of MUCLIM3 are modified accordingly. Simulations show that the urban model MUCLIM3 is able to capture typical observed characteristics of urban climate of Istanbul qualitatively. The UHI effect at night is stronger at low wind speeds, depending on the two competing factors: reduced cold advection from outlying rural areas and the magnitude of the sensible heat flux over cities which offsets the reduced advective cooling. The preliminary results of the sensitivity tests are discussed by concentrating on the changes of the hot spots in Istanbul, the diurnal cycle range over different land use types at different reference levels of 5m, 30m and 50m, and the vertical profile of the meteorological variables in relation to the sea-breeze circulation. This work is funded by the ERAfrica Project LOCLIM3 and TUBITAK with the Grant Number 114Y047.

Investigating the Impact of Surface Heterogeneity on the Convective Boundary Layer Over Urban Areas Through Coupled Large-Eddy Simulation and Remote Sensing

NASA Technical Reports Server (NTRS)

Dominguez, Anthony; Kleissl, Jan P.; Luvall, Jeffrey C.

2011-01-01

Large-eddy Simulation (LES) was used to study convective boundary layer (CBL) flow through suburban regions with both large and small scale heterogeneities in surface temperature. Constant remotely sensed surface temperatures were applied at the surface boundary at resolutions of 10 m, 90 m, 200 m, and 1 km. Increasing the surface resolution from 1 km to 200 m had the most significant impact on the mean and turbulent flow characteristics as the larger scale heterogeneities became resolved. While previous studies concluded that scales of heterogeneity much smaller than the CBL inversion height have little impact on the CBL characteristics, we found that further increasing the surface resolution (resolving smaller scale heterogeneities) results in an increase in mean surface heat flux, thermal blending height, and potential temperature profile. The results of this study will help to better inform sub-grid parameterization for meso-scale meteorological models. The simulation tool developed through this study (combining LES and high resolution remotely sensed surface conditions) is a significant step towards future studies on the micro-scale meteorology in urban areas.

Generating Accurate Urban Area Maps from Nighttime Satellite (DMSP/OLS) Data

NASA Technical Reports Server (NTRS)

Imhoff, Marc; Lawrence, William; Elvidge, Christopher

2000-01-01

There has been an increasing interest by the international research community to use the nighttime acquired "city-lights" data sets collected by the US Defense Meteorological Satellite Program's Operational Linescan system to study issues relative to urbanization. Many researchers are interested in using these data to estimate human demographic parameters over large areas and then characterize the interactions between urban development , natural ecosystems, and other aspects of the human enterprise. Many of these attempts rely on an ability to accurately identify urbanized area. However, beyond the simple determination of the loci of human activity, using these data to generate accurate estimates of urbanized area can be problematic. Sensor blooming and registration error can cause large overestimates of urban land based on a simple measure of lit area from the raw data. We discuss these issues, show results of an attempt to do a historical urban growth model in Egypt, and then describe a few basic processing techniques that use geo-spatial analysis to threshold the DMSP data to accurately estimate urbanized areas. Algorithm results are shown for the United States and an application to use the data to estimate the impact of urban sprawl on sustainable agriculture in the US and China is described.

Canopy rainfall partitioning across an urbanization gradient in forest structure as characterized by terrestrial LiDAR

NASA Astrophysics Data System (ADS)

Mesta, D. C.; Van Stan, J. T., II; Yankine, S. A.; Cote, J. F.; Jarvis, M. T.; Hildebrandt, A.; Friesen, J.; Maldonado, G.

2017-12-01

As urbanization expands, greater forest area is shifting from natural stand structures to urban stand structures, like forest fragments and landscaped tree rows. Changes in forest canopy structure have been found to drastically alter the amount of rainwater reaching the surface. However, stormwater management models generally treat all forest structures (beyond needle versus broadleaved) similarly. This study examines the rainfall partitioning of Pinus spp. canopies along a natural-to-urban forest gradient and compares these to canopy structural measurements using terrestrial LiDAR. Throughfall and meteorological observations were also used to estimate parameters of the commonly-used Gash interception model. Preliminary findings indicate that as forest structure changed from natural, closed canopy conditions to semi-closed canopy fragments and, ultimately, to exposed urban landscaping tree rows, the interchange between throughfall and rainfall interception also changed. This shift in partitioning between throughfall and rainfall interception may be linked to intuitive parameters, like canopy closure and density, as well as more complex metrics, like the fine-scale patterning of gaps (ie, lacunarity). Thus, results indicate that not all forests of the same species should be treated the same by stormwater models. Rather, their canopy structural characteristics should be used to vary their hydrometeorological interactions.

An Investigation of the Influence of Urban Areas on Rainfall Using the TRMM Satellite and a Cloud-Mesoscale Model

NASA Astrophysics Data System (ADS)

Shepherd, J.

2002-05-01

A recent paper by Shepherd et al. (in press at Journal of Applied Meteorology) used rainfall data from the Precipitation Radar on NASA's Tropical Rainfall Measuring Mission's (TRMM) satellite to identify warm season rainfall anomalies downwind of major urban areas. Data (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas. Results are consistent with METROMEX studies of St. Louis almost two decades ago and with more recent studies near Atlanta. A convective-mesoscale model with extensive land-surface processes is currently being employed to (a) determine if an urban heat island (UHI) thermal perturbation can induce a dynamic response to affect rainfall processes and (b) quantify the impact of the following three factors on the evolution of rainfall: (1) urban surface roughness, (2) magnitude of the UHI temperature anomaly, and (3) physical size of the UHI temperature anomaly. The sensitivity experiments are achieved by inserting a slab of land with urban properties (e.g. roughness length, albedo, thermal character) within a rural surface environment and varying the appropriate lower boundary condition parameters. The study will discuss the feasibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. The talk also introduces very preliminary results from the modeling component of the study.

Retrieval of air temperatures from crowd-sourced battery temperatures of cell phones

NASA Astrophysics Data System (ADS)

Overeem, Aart; Robinson, James; Leijnse, Hidde; Uijlenhoet, Remko; Steeneveld, Gert-Jan; Horn, Berthold K. P.

2013-04-01

Accurate air temperature observations are important for urban meteorology, for example to study the urban heat island and adverse effects of high temperatures on human health. The number of available temperature observations is often relatively limited. A new development is presented to derive temperature information for the urban canopy from an alternative source: cell phones. Battery temperature data were collected by users of an Android application for cell phones (opensignal.com). The application automatically sends battery temperature data to a server for storage. In this study, battery temperatures are averaged in space and time to obtain daily averaged battery temperatures for each city separately. A regression model, which can be related to a physical model, is employed to retrieve daily air temperatures from battery temperatures. The model is calibrated with observed air temperatures from a meteorological station of an airport located in or near the city. Time series of air temperatures are obtained for each city for a period of several months, where 50% of the data is for independent verification. Results are presented for Buenos Aires, London, Los Angeles, Paris, Mexico City, Moscow, Rome, and Sao Paulo. The evolution of the retrieved air temperatures often correspond well with the observed ones. The mean absolute error of daily air temperatures is less than 2 degrees Celsius, and the bias is within 1 degree Celsius. This shows that monitoring air temperatures employing an Android application holds great promise. Since 75% of the world's population has a cell phone, 20% of the land surface of the earth has cellular telephone coverage, and 500 million devices use the Android operating system, there is a huge potential for measuring air temperatures employing cell phones. This could eventually lead to real-time world-wide temperature maps.

Impacts of urbanization and agricultural development on observed changes in surface air temperature over mainland China from 1961 to 2006

NASA Astrophysics Data System (ADS)

Han, Songjun; Tang, Qiuhong; Xu, Di; Yang, Zhiyong

2018-03-01

A large proportion of meteorological stations in mainland China are located in or near either urban or agricultural lands that were established throughout the period of rapid urbanization and agricultural development (1961-2006). The extent of the impacts of urbanization and agricultural development on observed air temperature changes across different climate regions remains elusive. This study evaluates the surface air temperature trends observed by 598 meteorological stations in relation to the urbanization and agricultural development over the arid northwest, semi-arid intermediate, and humid southeast regions of mainland China based on linear regressions of temperature trends on the fractions of urban and cultivated land within a 3-km radius of the stations. In all three regions, the stations surrounded by large urban land tend to experience rapid warming, especially at minimum temperature. This dependence is particularly significant in the southeast region, which experiences the most intense urbanization. In the northwest and intermediate regions, stations surrounded by large cultivated land encounter less warming during the main growing season, especially at the maximum temperature changes. These findings suggest that the observed surface warming has been affected by urbanization and agricultural development represented by urban and cultivated land fractions around stations in with land cover changes in their proximity and should thus be considered when analyzing regional temperature changes in mainland China.

Motor transport related harmful PM2.5 and PM10: from onroad measurements to the modelling of air pollution by neural network approach on street and urban level

NASA Astrophysics Data System (ADS)

Lozhkina, O.; Lozhkin, V.; Nevmerzhitsky, N.; Tarkhov, D.; Vasilyev, A.

2016-11-01

The level of PM10 and PM2.5 concentrations in the air on seven roads in St. Petersburg, Russia, were investigated using gravimetry and nephelometry measurement techniques in 2013-2015. The effects of meteorological conditions (temperature, relative humidity, wind direction, and speed) and the intensity of traffic flows on the results of the measurements were also evaluated. On the base of the measurements, there was developed a neural network modelling approach that allowed to quantify exhaust / non-exhaust PM10 and PM 2.5 emissions and carry out numerical investigations of air pollution by transport related PM2.5 and PM10 on street and urban level in St. Petersburg.

Modelling the urban air quality in Hamburg with the new city-scale chemistry transport model CityChem

NASA Astrophysics Data System (ADS)

Karl, Matthias; Ramacher, Martin; Aulinger, Armin; Matthias, Volker; Quante, Markus

2017-04-01

Air quality modelling plays an important role by providing guidelines for efficient air pollution abatement measures. Currently, most urban dispersion models treat air pollutants as passive tracer substances or use highly simplified chemistry when simulating air pollutant concentrations on the city-scale. The newly developed urban chemistry-transport model CityChem has the capability of modelling the photochemical transformation of multiple pollutants along with atmospheric diffusion to produce pollutant concentration fields for the entire city on a horizontal resolution of 100 m or even finer and a vertical resolution of 24 layers up to 4000 m height. CityChem is based on the Eulerian urban dispersion model EPISODE of the Norwegian Institute for Air Research (NILU). CityChem treats the complex photochemistry in cities using detailed EMEP chemistry on an Eulerian 3-D grid, while using simple photo-stationary equilibrium on a much higher resolution grid (receptor grid), i.e. close to industrial point sources and traffic sources. The CityChem model takes into account that long-range transport contributes to urban pollutant concentrations. This is done by using 3-D boundary concentrations for the city domain derived from chemistry-transport simulations with the regional air quality model CMAQ. For the study of the air quality in Hamburg, CityChem was set-up with a main grid of 30×30 grid cells of 1×1 km2 each and a receptor grid of 300×300 grid cells of 100×100 m2. The CityChem model was driven with meteorological data generated by the prognostic meteorology component of the Australian chemistry-transport model TAPM. Bottom-up inventories of emissions from traffic, industry, households were based on data of the municipality of Hamburg. Shipping emissions for the port of Hamburg were taken from the Clean North Sea Shipping project. Episodes with elevated ozone (O3) were of specific interest for this study, as these are associated with exceedances of the World Health Organization (WHO) guideline concentration limits for O3 and of the regulatory limits for NO2. Model tests were performed with CityChem to study the ozone formation rate with simultaneous variation of emissions of nitrogen oxides (NOx) and volatile organic compounds (VOC). Emissions of VOC in urban areas are not well quantified as they may originate from various sources, including solvent usage, industry, combustion plants and vehicular traffic. The employed chemical mechanism contains large uncertainties with respect to ozone formation. Observed high-O3 episodes were analyzed by comparing modelled pollutant concentrations with concentration data from the Hamburg air quality surveillance network (http://luft.hamburg.de/). The analysis inspected possible reasons for too low modelled O3 in summer such as missing emissions of VOC from natural sources like green parks and the vertical exchange of O3 towards the surface.

A Numerical Simulation of Traffic-Related Air Pollution Exposures in Urban Street Canyons

NASA Astrophysics Data System (ADS)

Liu, J.; Fu, X.; Tao, S.

2016-12-01

Urban street canyons are usually associated with intensive vehicle emissions. However, the high buildings successively along both sides of a street block the dispersion of traffic-generated air pollutants, which enhances human exposure and adversely affects human health. In this study, an urban scale traffic pollution dispersion model is developed with the consideration of street distribution, canyon geometry, background meteorology, traffic assignment, traffic emissions and air pollutant dispersion. Vehicle exhausts generated from traffic flows will first disperse inside a street canyon along the micro-scale wind field (generated by computational fluid dynamics (CFD) model) and then leave the street canyon and further disperse over the urban area. On the basis of this model, the effects of canyon geometry on the distribution of NOx and CO from traffic emissions were studied over the center of Beijing, China. We found that an increase of building height along the streets leads to higher pollution levels inside streets and lower pollution levels outside, resulting in higher domain-averaged concentrations over the area. In addition, street canyons with equal (or highly uneven) building heights on two sides of a street tend to lower the urban-scale air pollution concentrations at pedestrian level. Our results indicate that canyon geometry strongly influences human exposure to traffic pollutants in the populated urban area. Carefully planning street layout and canyon geometry in consideration of traffic demand as well as local weather pattern may significantly reduce the chances of unhealthy air being inhaled by urban residents.

Ozone in the southeastern United States: An observation-based model using measurements from the SEARCH network

NASA Astrophysics Data System (ADS)

Blanchard, C. L.; Hidy, G. M.; Tanenbaum, S.

2014-05-01

A generalized additive model (GAM) is used to examine the influence of meteorological factors, nitrogen oxides (NOx = NO + NO2), and non-methane hydrocarbons (NMOC) on daily peak 8-h ozone (O3) concentrations. Application to 2002-2011 monitoring data from the Southeastern Aerosol Research and Characterization (SEARCH) program showed sensitivity of peak 8-h O3 to morning concentrations of nitric oxide (NO) and nitrogen dioxide (NO2) and to afternoon concentrations of NO2 reaction products (NOz). Peak O3 decreased with increasing NO and increased with increasing NO2 concentrations, consistent with reactions involving O3, NO, and NO2. Ozone production efficiency (OPE), estimated from the modeled relation between peak 8-h O3 and afternoon NOz, was ˜40-100 percent higher at rural compared to urban sites. OPE was nonlinear at all sites, decreasing with increasing NOz concentration. The mean ratio of NOz/NOy showed a two-fold increase from urban to rural sites, associated with chemical aging in stagnant air masses from one day (urban sites) to two or more days (non-urban sites). Peak 8-h O3 concentrations in Atlanta were sensitive to concentrations of both non-biogenic NMOC and NOz. Non-urban Yorkville, Georgia, peak 8-h O3 concentrations were sensitive to NOz but not to non-biogenic NMOC concentrations. The results are consistent with expected NMOC and NOx sensitivity in urban and non-urban locales.

Aerosol physicochemical properties in relation to meteorology: Case studies in urban, marine, and arid settings

NASA Astrophysics Data System (ADS)

Wonaschuetz, Anna

Atmospheric aerosols are a highly relevant component of the climate system affecting atmospheric radiative transfer and the hydrological cycle. As opposed to other key atmospheric constituents with climatic relevance, atmospheric aerosol particles are highly heterogeneous in time and space with respect to their size, concentration, chemical composition and physical properties. Many aspects of their life cycle are not understood, making them difficult to represent in climate models and hard to control as a pollutant. Aerosol-cloud interactions in particular are infamous as a major source of uncertainty in future climate predictions. Field measurements are an important source of information for the modeling community and can lead to a better understanding of chemical and microphysical processes. In this study, field data from urban, marine, and arid settings are analyzed and the impact of meteorological conditions on the evolution of aerosol particles while in the atmosphere is investigated. Particular attention is given to organic aerosols, which are a poorly understood component of atmospheric aerosols. Local wind characteristics, solar radiation, relative humidity and the presence or absence of clouds and fog are found to be crucial factors in the transport and chemical evolution of aerosol particles. Organic aerosols in particular are found to be heavily impacted by processes in the liquid phase (cloud droplets and aerosol water). The reported measurements serve to improve the process-level understanding of aerosol evolution in different environments and to inform the modeling community by providing realistic values for input parameters and validation of model calculations.

A New Type of Captive Balloon for Vertical Meteorological Observation in Urban Area

NASA Astrophysics Data System (ADS)

Nakamura, M.; Sakai, S.; Ono, K.

2010-12-01

Many meteorological observations in urban area have been made in recent years in order to investigate the mechanism of heat island. However, there are few data of cooling process in urban area. For this purpose, high density observations in both space and time are required. Generally vertical meteorological observations can be made by towers, radars, balloons. These methods are limited by urban area conditions. Among these methods, a captive balloon is mainly used to about a hundred meter from ground in a vertical meteorological observation. Small airships called kytoons or advertising balloons, for example. Conventional balloons are, however, influenced by the wind and difficult to keep the specified position. Moreover, it can be dangerous to conduct such observations in the highly build-up area. To overcome these difficulties, we are developing a new type of captive balloon. It has a wing form to gain lift and keep its position. It is also designed small to be kept in a carport. It is made of aluminum film and polyester cloth in order to attain lightweight solution. We have tried floating a balloon like NACA4424 for several years. It was difficult to keep a wing form floating up over 100 meters from ground because internal pressure was decreased by different temperature. The design is changed in this year. The balloon that has wing form NACA4415 is similar in composition to an airplane. It has a big gasbag with airship form and two wing form. It is able to keep form of a wing by high internal pressure. We will report a plan for the balloon and instances of some observations.

Modeling of the anthropogenic heat flux and its effect on regional meteorology and air quality over the Yangtze River Delta region, China

NASA Astrophysics Data System (ADS)

Xie, Min; Liao, Jingbiao; Wang, Tijian; Zhu, Kuanguang; Zhuang, Bingliang; Han, Yong; Li, Mengmeng; Li, Shu

2016-05-01

Anthropogenic heat (AH) emissions from human activities caused by urbanization can affect the city environment. Based on the energy consumption and the gridded demographic data, the spatial distribution of AH emission over the Yangtze River Delta (YRD) region is estimated. Meanwhile, a new method for the AH parameterization is developed in the WRF/Chem model, which incorporates the gridded AH emission data with the seasonal and diurnal variations into the simulations. By running this upgraded WRF/Chem for 2 typical months in 2010, the impacts of AH on the meteorology and air quality over the YRD region are studied. The results show that the AH fluxes over the YRD have been growing in recent decades. In 2010, the annual-mean values of AH over Shanghai, Jiangsu and Zhejiang are 14.46, 2.61 and 1.63 W m-2, respectively, with the high value of 113.5 W m-2 occurring in the urban areas of Shanghai. These AH emissions can significantly change the urban heat island and urban-breeze circulations in the cities of the YRD region. In Shanghai, 2 m air temperature increases by 1.6 °C in January and 1.4 °C in July, the PBLH (planetary boundary layer height) rises up by 140 m in January and 160 m in July, and 10 m wind speed is enhanced by 0.7 m s-1 in January and 0.5 m s-1 in July, with a higher increment at night. The enhanced vertical movement can transport more moisture to higher levels, which causes the decrease in water vapor at ground level and the increase in the upper PBL (planetary boundary layer), and thereby induces the accumulative precipitation to increase by 15-30 % over the megacities in July. The adding of AH can impact the spatial and vertical distributions of the simulated pollutants as well. The concentrations of primary air pollutants decrease near the surface and increase at the upper levels, due mainly to the increases in PBLH, surface wind speed and upward air vertical movement. But surface O3 concentrations increase in the urban areas, with maximum changes of 2.5 ppb in January and 4 ppb in July. Chemical direct (the rising up of air temperature directly accelerates surface O3 formation) and indirect (the decrease in NOx at the ground results in the increase in surface O3) effects can play a significant role in O3 changes over this region. The meteorology and air pollution predictions in and around large urban areas are highly sensitive to the anthropogenic heat inputs, suggesting that AH should be considered in the climate and air quality assessments.

Contributions to Global Augmented Compound Urban Heat Extreme (ACUTE) from Climate Change and the Urban Heat Island Effect

NASA Astrophysics Data System (ADS)

Huang, K.

2017-12-01

Over the next decades, climate change is projected to increase the intensity and frequency of extreme heat events (EHEs). The severity and periodicity of these hazards are likely to be further compounded by stronger urban heat island (UHI) effects as the world continues to urbanize. However, there is little known about how greenhouse gases (GHG) induced changes in EHE will interact with UHI, and what this will mean for the exposure of urban populations to high temperature. This work aims to fill this knowledge gap by combining a mesoscale meteorological model (Weather Research Forecasting, WRF) with a global urban expansion forecast, to generate spatially explicit projections of compound urban temperature extremes through 2050. These global projections include all the urban areas in developing world. The respective contributions from GHG-induced climate change, the UHI effect, and their interaction vary across different types of urban areas. The resulting compound heat extremes will be more intense and frequent in emerging Asian and African mega urban regions, located in tropical/subtropical climates, due to their unprecedented sizes and the significantly reduced evaporation. Previous studies neglecting the interaction between global climate change and regional UHI effect have underestimated exposure to heat extremes in urban areas.

Decadal evaluation of regional climate, air quality, and their interactions over the continental US and their interactions using WRF/Chem version 3.6.1

NASA Astrophysics Data System (ADS)

Yahya, Khairunnisa; Wang, Kai; Campbell, Patrick; Glotfelty, Timothy; He, Jian; Zhang, Yang

2016-02-01

The Weather Research and Forecasting model with Chemistry (WRF/Chem) v3.6.1 with the Carbon Bond 2005 (CB05) gas-phase mechanism is evaluated for its first decadal application during 2001-2010 using the Representative Concentration Pathway 8.5 (RCP 8.5) emissions to assess its capability and appropriateness for long-term climatological simulations. The initial and boundary conditions are downscaled from the modified Community Earth System Model/Community Atmosphere Model (CESM/CAM5) v1.2.2. The meteorological initial and boundary conditions are bias-corrected using the National Center for Environmental Protection's Final (FNL) Operational Global Analysis data. Climatological evaluations are carried out for meteorological, chemical, and aerosol-cloud-radiation variables against data from surface networks and satellite retrievals. The model performs very well for the 2 m temperature (T2) for the 10-year period, with only a small cold bias of -0.3 °C. Biases in other meteorological variables including relative humidity at 2 m, wind speed at 10 m, and precipitation tend to be site- and season-specific; however, with the exception of T2, consistent annual biases exist for most of the years from 2001 to 2010. Ozone mixing ratios are slightly overpredicted at both urban and rural locations with a normalized mean bias (NMB) of 9.7 % but underpredicted at rural locations with an NMB of -8.8 %. PM2.5 concentrations are moderately overpredicted with an NMB of 23.3 % at rural sites but slightly underpredicted with an NMB of -10.8 % at urban/suburban sites. In general, the model performs relatively well for chemical and meteorological variables, and not as well for aerosol-cloud-radiation variables. Cloud-aerosol variables including aerosol optical depth, cloud water path, cloud optical thickness, and cloud droplet number concentration are generally underpredicted on average across the continental US. Overpredictions of several cloud variables over the eastern US result in underpredictions of radiation variables (such as net shortwave radiation - GSW - with a mean bias - MB - of -5.7 W m-2) and overpredictions of shortwave and longwave cloud forcing (MBs of ˜ 7 to 8 W m-2), which are important climate variables. While the current performance is deemed to be acceptable, improvements to the bias-correction method for CESM downscaling and the model parameterizations of cloud dynamics and thermodynamics, as well as aerosol-cloud interactions, can potentially improve model performance for long-term climate simulations.

Developing a landscape of urban building energy use with improved spatiotemporal representations in a cool-humid climate

DOE PAGES

Li, Wenliang; Zhou, Yuyu; Cetin, Kristen S.; ...

2018-03-24

Urban buildings account for up to 75% of total energy use in the United States (U.S.). Understanding urban building energy use is important for developing feasible options to mitigate energy use and greenhouse gas emissions. In this study, an improved bottom-up building energy use model, named City Building Energy Use Model (CityBEUM), was developed to estimate building energy use for all buildings in Polk County, Iowa. First, 28 commercial and 6 residential building prototypes were designed by combing Assessor's parcel data and building footprint data. Then, the EnergyPlus in the CityBEUM was calibrated for all building prototypes using the U.S.more » Energy Information Administration's survey data, monthly utility meter data, and actual weather data. Finally, spatial and temporal variations of building energy use in the study area were estimated using the CityBEUM. Results indicate that the spatial variation of building energy use in the study area can be captured using the CityBEUM. With the monthly-calibrated model, the temporal pattern of urban building energy use can be well represented. The comparison of building energy use using the Typical Meteorological Year and actual weather data demonstrates the importance of using actual weather data in building energy modeling for an improved temporal representation.« less

Developing a landscape of urban building energy use with improved spatiotemporal representations in a cool-humid climate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Wenliang; Zhou, Yuyu; Cetin, Kristen S.

Urban buildings account for up to 75% of total energy use in the United States (U.S.). Understanding urban building energy use is important for developing feasible options to mitigate energy use and greenhouse gas emissions. In this study, an improved bottom-up building energy use model, named City Building Energy Use Model (CityBEUM), was developed to estimate building energy use for all buildings in Polk County, Iowa. First, 28 commercial and 6 residential building prototypes were designed by combing Assessor's parcel data and building footprint data. Then, the EnergyPlus in the CityBEUM was calibrated for all building prototypes using the U.S.more » Energy Information Administration's survey data, monthly utility meter data, and actual weather data. Finally, spatial and temporal variations of building energy use in the study area were estimated using the CityBEUM. Results indicate that the spatial variation of building energy use in the study area can be captured using the CityBEUM. With the monthly-calibrated model, the temporal pattern of urban building energy use can be well represented. The comparison of building energy use using the Typical Meteorological Year and actual weather data demonstrates the importance of using actual weather data in building energy modeling for an improved temporal representation.« less

Spatio-temporal modeling of chronic PM 10 exposure for the Nurses' Health Study

NASA Astrophysics Data System (ADS)

Yanosky, Jeff D.; Paciorek, Christopher J.; Schwartz, Joel; Laden, Francine; Puett, Robin; Suh, Helen H.

2008-06-01

Chronic epidemiological studies of airborne particulate matter (PM) have typically characterized the chronic PM exposures of their study populations using city- or county-wide ambient concentrations, which limit the studies to areas where nearby monitoring data are available and which ignore within-city spatial gradients in ambient PM concentrations. To provide more spatially refined and precise chronic exposure measures, we used a Geographic Information System (GIS)-based spatial smoothing model to predict monthly outdoor PM10 concentrations in the northeastern and midwestern United States. This model included monthly smooth spatial terms and smooth regression terms of GIS-derived and meteorological predictors. Using cross-validation and other pre-specified selection criteria, terms for distance to road by road class, urban land use, block group and county population density, point- and area-source PM10 emissions, elevation, wind speed, and precipitation were found to be important determinants of PM10 concentrations and were included in the final model. Final model performance was strong (cross-validation R2=0.62), with little bias (-0.4 μg m-3) and high precision (6.4 μg m-3). The final model (with monthly spatial terms) performed better than a model with seasonal spatial terms (cross-validation R2=0.54). The addition of GIS-derived and meteorological predictors improved predictive performance over spatial smoothing (cross-validation R2=0.51) or inverse distance weighted interpolation (cross-validation R2=0.29) methods alone and increased the spatial resolution of predictions. The model performed well in both rural and urban areas, across seasons, and across the entire time period. The strong model performance demonstrates its suitability as a means to estimate individual-specific chronic PM10 exposures for large populations.

The urban heat island in a small city in coastal Portugal.

PubMed

Pinho, O S; Orgaz, M D

2000-11-01

This project arose from the need to study the phenomenon of the urban heat island, since only by recognising this phenomenon can we moderate it to improve the human and urban environments. Not only big cities develop urban heat islands. This study detected the presence and recorded the characteristics of an urban heat island in the small coastal city of Aveiro, Portugal. The study was developed through the scheduled measurements of air temperature and the analysis of the geographical, meteorological and urban conditions. The form and intensity of Aveiro's heat island are a response to the interaction of three principal factors: the urban morphology (the hottest zones in the city are those with the tallest and the highest density of buildings, without green spaces and with intense generation of heat from traffic, commerce and services); the meteorological conditions (the intensity of the island is at its maximum when the sky is totally clear and there is no wind, and at its minimum in those situations when there is atmospheric instability, such as wind, cloud and precipitation); and the proximity of the coastal lagoon (which borders the city to the west and northwest and moderates seasonal temperatures. The urban heat island influences the comfort and health of its inhabitants, thus urban planning is very important in the moderation and prevention of this phenomenon.

Probabilistic forecasts based on radar rainfall uncertainty

NASA Astrophysics Data System (ADS)

Liguori, S.; Rico-Ramirez, M. A.

2012-04-01

The potential advantages resulting from integrating weather radar rainfall estimates in hydro-meteorological forecasting systems is limited by the inherent uncertainty affecting radar rainfall measurements, which is due to various sources of error [1-3]. The improvement of quality control and correction techniques is recognized to play a role for the future improvement of radar-based flow predictions. However, the knowledge of the uncertainty affecting radar rainfall data can also be effectively used to build a hydro-meteorological forecasting system in a probabilistic framework. This work discusses the results of the implementation of a novel probabilistic forecasting system developed to improve ensemble predictions over a small urban area located in the North of England. An ensemble of radar rainfall fields can be determined as the sum of a deterministic component and a perturbation field, the latter being informed by the knowledge of the spatial-temporal characteristics of the radar error assessed with reference to rain-gauges measurements. This approach is similar to the REAL system [4] developed for use in the Southern-Alps. The radar uncertainty estimate can then be propagated with a nowcasting model, used to extrapolate an ensemble of radar rainfall forecasts, which can ultimately drive hydrological ensemble predictions. A radar ensemble generator has been calibrated using radar rainfall data made available from the UK Met Office after applying post-processing and corrections algorithms [5-6]. One hour rainfall accumulations from 235 rain gauges recorded for the year 2007 have provided the reference to determine the radar error. Statistics describing the spatial characteristics of the error (i.e. mean and covariance) have been computed off-line at gauges location, along with the parameters describing the error temporal correlation. A system has then been set up to impose the space-time error properties to stochastic perturbations, generated in real-time at gauges location, and then interpolated back onto the radar domain, in order to obtain probabilistic radar rainfall fields in real time. The deterministic nowcasting model integrated in the STEPS system [7-8] has been used for the purpose of propagating the uncertainty and assessing the benefit of implementing the radar ensemble generator for probabilistic rainfall forecasts and ultimately sewer flow predictions. For this purpose, events representative of different types of precipitation (i.e. stratiform/convective) and significant at the urban catchment scale (i.e. in terms of sewer overflow within the urban drainage system) have been selected. As high spatial/temporal resolution is required to the forecasts for their use in urban areas [9-11], the probabilistic nowcasts have been set up to be produced at 1 km resolution and 5 min intervals. The forecasting chain is completed by a hydrodynamic model of the urban drainage network. The aim of this work is to discuss the implementation of this probabilistic system, which takes into account the radar error to characterize the forecast uncertainty, with consequent potential benefits in the management of urban systems. It will also allow a comparison with previous findings related to the analysis of different approaches to uncertainty estimation and quantification in terms of rainfall [12] and flows at the urban scale [13]. Acknowledgements The authors would like to acknowledge the BADC, the UK Met Office and Dr. Alan Seed from the Australian Bureau of Meteorology for providing the radar data and the nowcasting model. The authors acknowledge the support from the Engineering and Physical Sciences Research Council (EPSRC) via grant EP/I012222/1.

The relation between land-cover and the urban heat island in northeastern Puerto Rico

Treesearch

David J.R. Murphy; Myrna Hall; Charles Hall; Gordon Heisler; Steve Stehman

2007-01-01

As development continues in Puerto Rico, forests and grasslands are being converted to impervious cover, changing the magnitude and geographic range of the Urban Heat Island (UHI). As part of the U.S. National Science Foundation Long Term Ecological Research Program, this study aims to quantify the various meteorological effects that urbanization may be imparting on...

A review of ion and metal pollutants in urban green water infrastructures.

PubMed

Kabir, Md Imran; Daly, Edoardo; Maggi, Federico

2014-02-01

In urban environments, the breakdown of chemicals and pollutants, especially ions and metal compounds, can be favoured by green water infrastructures (GWIs). The overall aim of this review is to set the basis to model GWIs using deterministic approaches in contrast to empirical ones. If a better picture of chemicals and pollutant input and an improved understanding of hydrological and biogeochemical processes affecting these pollutants were known, GWIs could be designed to efficiently retain these pollutants for site-specific meteorological patterns and pollutant load. To this end, we surveyed the existing literature to retrieve a comprehensive dataset of anions and cations, and alkaline and transition metal pollutants incoming to urban environments. Based on this survey, we assessed the pollution load and ecological risk indexes for metals. The existing literature was then surveyed to review the metal retention efficiency of GWIs, and possible biogeochemical processes related to inorganic metal compounds were proposed that could be integrated in biogeochemical models of GWIs. © 2013.

Modelling the dispersion and transport of reactive pollutants in a deep urban street canyon: using large-eddy simulation.

PubMed

Zhong, Jian; Cai, Xiao-Ming; Bloss, William James

2015-05-01

This study investigates the dispersion and transport of reactive pollutants in a deep urban street canyon with an aspect ratio of 2 under neutral meteorological conditions using large-eddy simulation. The spatial variation of pollutants is significant due to the existence of two unsteady vortices. The deviation of species abundance from chemical equilibrium for the upper vortex is greater than that for the lower vortex. The interplay of dynamics and chemistry is investigated using two metrics: the photostationary state defect, and the inferred ozone production rate. The latter is found to be negative at all locations within the canyon, pointing to a systematic negative offset to ozone production rates inferred by analogous approaches in environments with incomplete mixing of emissions. This study demonstrates an approach to quantify parameters for a simplified two-box model, which could support traffic management and urban planning strategies and personal exposure assessment. Copyright © 2015 Elsevier Ltd. All rights reserved.

Patterns of Bacillary Dysentery in China, 2005-2010.

PubMed

Zhang, Han; Si, Yali; Wang, Xiaofeng; Gong, Peng

2016-01-27

Although the incidence of bacillary dysentery in China has been declining progressively, a considerable disease burden still exists. Few studies have analyzed bacillary dysentery across China and knowledge gaps still exist in the aspects of geographic distribution and ecological drivers, seasonality and its association with meteorological factors, urban-rural disparity, prevalence and distribution of Shigella species. Here, we performed nationwide analyses to fill the above gaps. Geographically, we found that incidence increased along an east-west gradient which was inversely related to the economic conditions of China. Two large endemically high-risk regions in western China and their ecological drivers were identified for the first time. We characterized seasonality of bacillary dysentery incidence and assessed its association with meteorological factors, and saw that it exhibits north-south differences in peak duration, relative amplitude and key meteorological factors. Urban and rural incidences among China's cities were compared, and disparity associated with urbanization level was invariant in most cities. Balanced decrease of urban and rural incidence was observed for all provinces except Hunan. S. flexneri and S. sonnei were identified as major causative species. Increasing prevalence of S. sonnei and geographic distribution of Shigella species were associated with economic status. Findings and inferences from this study draw broader pictures of bacillary dysentery in mainland China and could provide useful information for better interventions and public health planning.

Patterns of Bacillary Dysentery in China, 2005–2010

PubMed Central

Zhang, Han; Si, Yali; Wang, Xiaofeng; Gong, Peng

2016-01-01

Although the incidence of bacillary dysentery in China has been declining progressively, a considerable disease burden still exists. Few studies have analyzed bacillary dysentery across China and knowledge gaps still exist in the aspects of geographic distribution and ecological drivers, seasonality and its association with meteorological factors, urban-rural disparity, prevalence and distribution of Shigella species. Here, we performed nationwide analyses to fill the above gaps. Geographically, we found that incidence increased along an east-west gradient which was inversely related to the economic conditions of China. Two large endemically high-risk regions in western China and their ecological drivers were identified for the first time. We characterized seasonality of bacillary dysentery incidence and assessed its association with meteorological factors, and saw that it exhibits north-south differences in peak duration, relative amplitude and key meteorological factors. Urban and rural incidences among China’s cities were compared, and disparity associated with urbanization level was invariant in most cities. Balanced decrease of urban and rural incidence was observed for all provinces except Hunan. S. flexneri and S. sonnei were identified as major causative species. Increasing prevalence of S. sonnei and geographic distribution of Shigella species were associated with economic status. Findings and inferences from this study draw broader pictures of bacillary dysentery in mainland China and could provide useful information for better interventions and public health planning. PMID:26828503

Weather Variability Associated with Aedes (Stegomyia) aegypti (Dengue Vector) Oviposition Dynamics in Northwestern Argentina

PubMed Central

Estallo, Elizabet L.; Ludueña-Almeida, Francisco F.; Introini, María V.; Zaidenberg, Mario; Almirón, Walter R.

2015-01-01

This study aims to develop a forecasting model by assessing the weather variability associated with seasonal fluctuation of Aedes aegypti oviposition dynamic at a city level in Orán, in northwestern Argentina. Oviposition dynamics were assessed by weekly monitoring of 90 ovitraps in the urban area during 2005-2007. Correlations were performed between the number of eggs collected weekly and weather variables (rainfall, photoperiod, vapor pressure of water, temperature, and relative humidity) with and without time lags (1 to 6 weeks). A stepwise multiple linear regression analysis was performed with the set of meteorological variables from the first year of study with the variables in the time lags that best correlated with the oviposition. Model validation was conducted using the data from the second year of study (October 2006- 2007). Minimum temperature and rainfall were the most important variables. No eggs were found at temperatures below 10°C. The most significant time lags were 3 weeks for minimum temperature and rains, 3 weeks for water vapor pressure, and 6 weeks for maximum temperature. Aedes aegypti could be expected in Orán three weeks after rains with adequate min temperatures. The best-fit forecasting model for the combined meteorological variables explained 70 % of the variance (adj. R2). The correlation between Ae. aegypti oviposition observed and estimated by the forecasting model resulted in rs = 0.80 (P < 0.05). The forecasting model developed would allow prediction of increases and decreases in the Ae. aegypti oviposition activity based on meteorological data for Orán city and, according to the meteorological variables, vector activity can be predicted three or four weeks in advance. PMID:25993415

Integrating a street-canyon model with a regional Gaussian dispersion model for improved characterisation of near-road air pollution

NASA Astrophysics Data System (ADS)

Fallah-Shorshani, Masoud; Shekarrizfard, Maryam; Hatzopoulou, Marianne

2017-03-01

The development and use of dispersion models that simulate traffic-related air pollution in urban areas has risen significantly in support of air pollution exposure research. In order to accurately estimate population exposure, it is important to generate concentration surfaces that take into account near-road concentrations as well as the transport of pollutants throughout an urban region. In this paper, an integrated modelling chain was developed to simulate ambient Nitrogen Dioxide (NO2) in a dense urban neighbourhood while taking into account traffic emissions, the regional background, and the transport of pollutants within the urban canopy. For this purpose, we developed a hybrid configuration including 1) a street canyon model, which simulates pollutant transfer along streets and intersections, taking into account the geometry of buildings and other obstacles, and 2) a Gaussian puff model, which resolves the transport of contaminants at the top of the urban canopy and accounts for regional meteorology. Each dispersion model was validated against measured concentrations and compared against the hybrid configuration. Our results demonstrate that the hybrid approach significantly improves the output of each model on its own. An underestimation appears clearly for the Gaussian model and street-canyon model compared to observed data. This is due to ignoring the building effect by the Gaussian model and undermining the contribution of other roads by the canyon model. The hybrid approach reduced the RMSE (of observed vs. predicted concentrations) by 16%-25% compared to each model on its own, and increased FAC2 (fraction of predictions within a factor of two of the observations) by 10%-34%.

Modeling thermal sensation in a Mediterranean climate—a comparison of linear and ordinal models

NASA Astrophysics Data System (ADS)

Pantavou, Katerina; Lykoudis, Spyridon

2014-08-01

A simple thermo-physiological model of outdoor thermal sensation adjusted with psychological factors is developed aiming to predict thermal sensation in Mediterranean climates. Microclimatic measurements simultaneously with interviews on personal and psychological conditions were carried out in a square, a street canyon and a coastal location of the greater urban area of Athens, Greece. Multiple linear and ordinal regression were applied in order to estimate thermal sensation making allowance for all the recorded parameters or specific, empirically selected, subsets producing so-called extensive and empirical models, respectively. Meteorological, thermo-physiological and overall models - considering psychological factors as well - were developed. Predictions were improved when personal and psychological factors were taken into account as compared to meteorological models. The model based on ordinal regression reproduced extreme values of thermal sensation vote more adequately than the linear regression one, while the empirical model produced satisfactory results in relation to the extensive model. The effects of adaptation and expectation on thermal sensation vote were introduced in the models by means of the exposure time, season and preference related to air temperature and irradiation. The assessment of thermal sensation could be a useful criterion in decision making regarding public health, outdoor spaces planning and tourism.

A Comparison of One-Dimensional Hydrologic Models Using Soil Moisture Observations under Urban Irrigation in a Desert Climate

NASA Astrophysics Data System (ADS)

Volo, T. J.; Vivoni, E. R.; Martin, C. A.; Wang, Z.; Ruddell, B.

2012-12-01

Through the past several decades, rapid population growth in the arid American Southwest has dramatically changed patterns of plant-available water through municipal and residential irrigation systems that provide supplemental water to designed and managed urban landscape vegetation. Urban irrigation, including diversion of rainwater and addition of imported water, has thereby enabled the transformation of areas once covered by bare soil and low water-use, native desert plant species to large tracts of exotic, high water-use turf grass and shade trees. Despite the large percentage of residential water appropriated to irrigation purposes, models of urban hydrology often fail to include the impact that this anthropogenic input has on water, energy, and biomass conditions. This study utilizes two one-dimensional soil moisture models to examine the importance of representing different processes in a quantitative urban ecohydrology model under irrigation scenarios. Such processes include sub-daily energy fluxes, vertical redistribution of soil moisture, saturation- and infiltration-excess runoff mechanisms, seasonally variable irrigation scheduling, and soil moisture control on evapotranspiration rates. The analysis is informed by soil moisture observations from an experimental sensor network in the Phoenix, Arizona metropolitan area. The network includes data from several different landscape and irrigation treatments representative of pre- and post-development conditions in the region. By interpreting soil moisture levels in terms of plant water stress, this study analyzes the effectiveness of urban irrigation practices in arid climates. Furthermore, by identifying the necessary hydrologic processes to represent in an urban ecohydrology model, our results inform future work in adapting a distributed hydrologic model to desert urban settings where irrigation plays a significant role in minimizing plant water stress. An appropriate model of water and energy balances, calibrated using local meteorological forcing, can facilitate discussions with water managers and homeowners regarding optimal irrigation frequency, volume, duration, and seasonality for individual landscapes, while also aiding in water-efficient landscape design for growing cities in desert regions.

Air Quality and Meteorological Boundary Conditions during the MCMA-2003 Field Campaign

NASA Astrophysics Data System (ADS)

Sosa, G.; Arriaga, J.; Vega, E.; Magaña, V.; Caetano, E.; de Foy, B.; Molina, L. T.; Molina, M. J.; Ramos, R.; Retama, A.; Zaragoza, J.; Martínez, A. P.; Márquez, C.; Cárdenas, B.; Lamb, B.; Velasco, E.; Allwine, E.; Pressley, S.; Westberg, H.; Reyes, R.

2004-12-01

A comprehensive field campaign to characterize photochemical smog in the Mexico City Metropolitan Area (MCMA) was conducted during April 2003. An important number of equipment was deployed all around the urban core and its surroundings to measure gas and particles composition from the various sources and receptor sites. In addition to air quality measurements, meteorology variables were also taken by regular weather meteorological stations, tethered balloons, radiosondes, sodars and lidars. One important issue with regard to the field campaign was the characterization of the boundary conditions in order to feed meteorological and air quality models. Four boundary sites were selected to measure continuously criteria pollutants, VOC and meteorological variables at surface level. Vertical meteorological profiles were measured at three other sites : radiosondes in Tacubaya site were launched every six hours daily; tethered balloons were launched at CENICA and FES-Cuautitlan sites according to the weather conditions, and one sodar was deployed at UNAM site in the south of the city. Additionally to these measurements, two fixed meteorological monitoring networks deployed along the city were available to complement these measurements. In general, we observed that transport of pollutants from the city to the boundary sites changes every day, according to the coupling between synoptic and local winds. This effect were less important at elevated sites such as Cerro de la Catedral and ININ, where synoptic wind were more dominant during the field campaign. Also, local sources nearby boundary sites hide the influence of pollution coming from the city some days, particularly at the La Reforma site.

Comparing the urbanization and global warming impacts on extreme rainfall characteristics in Southern China Pearl River Delta megacity based on dynamical downscaling

NASA Astrophysics Data System (ADS)

Fung, K. Y.; Tam, C. Y.; Wang, Z.

2017-12-01

It is well known that urban land use can significantly influence the local temperature, precipitation and meteorology through altering land-atmosphere exchange of momentum, moisture and heat in urban areas. In recent decades, there has been a substantial increase ( 5-10%) on the intensity of extreme rainfall over Southeast China; it is projected to increase further according to the latest IPCC reports. In this study, we assess how urbanization and global warming together might impact on heavy precipitation characteristics over the highly urbanized Pearl River Delta (PRD) megacity, located in southern China. This is done by dynamically downscaling GFDL-ESM2M simulations for the present and future (RCP8.5) climate scenarios, using the Weather Research and Forecasting (WRF) model coupled with a single-layer urban canopy model (UCM). Over the PRD area, the WRF model is integrated at a resolution of 2km x 2km. To focus on extreme events, episodes covering daily rainfall intensity above the 99th percentile in Southeast China in the GFDL-ESM2M daily precipitation datasets were first identified. These extreme episodes were then dynamically downscaled in two parallel experiments with the following model designs: one with anthropogenic heat flux (AH) = 0 Wm-2 and the other with peak AH = 300 Wm-2 in the AH diurnal cycle over the urban domain. Results show that, with AH in urban area, the urban 2m-temperature can rise by about 2oC. This in turn leads to an increase of the mean as well as the extreme rain rates by 10-15% in urban domain. The latter is comparable to the impact of global warming alone, according to downscaling experiments for the RCP8.5 scenario. Implications of our results on urban effects on extreme rainfall under a warming background climate will be discussed.

Investigating the vertical dimension of Singapore's urban heat island through quadcopter platforms: an pilot study

NASA Astrophysics Data System (ADS)

Chow, Winston; Ho, Dawn

2016-04-01

In numerous cities, measurements of urban warmth in most urban heat island (UHI) studies are generally constrained towards surface or near-surface (<2 m above surface level) levels across horizontal variations in land use and land cover. However, there has been hitherto limited attention towards the measurement of vertical temperature profiles extending from the urban surface, urban canopy layer through to the urban boundary layer. Knowledge of these profiles, through (a.) how they vary over different local urban morphologies, and (b.) develop with respect to synoptic meteorological conditions, are important towards several aspects of UHI research; these include validating modelling urban canopy lapse rate profiles or estimating the growth of urban plumes. In this novel study, we utilised temperature sensor-loggers attached onto remote controlled aerial quadcopter platforms to measure urban temperature profiles up to 100 m above ground level in Singapore, which is a rapidly urbanizing major tropical metropolis. Three different land use/land cover categories were sampled; a high-rise residential estate, a university campus, and an urban park/green-space. Sorties were flown repeatedly at four different times - sunrise, noon, sunset and midnight. Initial results indicate significant variations in intra-site stability and inversion development between the urban canopy and boundary layers. These profiles are also temporally dynamic, depending on the time of day and larger-scale weather conditions.

Regional climate model assessment of the urban land-surface forcing over central Europe

NASA Astrophysics Data System (ADS)

Huszar, P.; Halenka, T.; Belda, M.; Zak, M.; Sindelarova, K.; Miksovsky, J.

2014-07-01

For the purpose of qualifying and quantifying the climate impact of cities and urban surfaces in general on climate of central Europe, the surface parameterization in regional climate model RegCM4 has been extended with the Single Layer Urban Canopy Model (SLUCM). A set of experiments was performed over the period of 2005-2009 for central Europe, either without considering urban surfaces or with the SLUCM treatment. Results show a statistically significant impact of urbanized surfaces on temperature (up to 1.5 K increase in summer) as well as on the boundary layer height (increases up to 50 m). Urbanization further influences surface wind with a winter decrease up to -0.6 m s-1, though both increases and decreases were detected in summer depending on the location relative to the cities and daytime (changes up to 0.3 m s-1). Urban surfaces significantly reduce evaporation and thus the humidity over the surface. This impacts the simulated summer precipitation rate, showing decrease over cities up to -2 mm day-1. Significant temperature increases are simulated over higher elevations as well, not only within the urban canopy layer. With the urban parameterization, the climate model better describes the diurnal temperature variation, reducing the cold afternoon and evening bias of RegCM4. Sensitivity experiments were carried out to quantify the response of the meteorological conditions to changes in the parameters specific to the urban environment such as street width, building height, albedo of the roofs and anthropogenic heat release. The results proved to be rather robust and the choice of the key SLUCM parameters impacts them only slightly (mainly temperature, boundary layer height and wind velocity). Statistically significant impacts are modeled not only over large urbanized areas, but the influence of the cities is also evident over rural areas without major urban surfaces. It is shown that this is the result of the combined effect of the distant influence of the cities and the influence of the minor local urban surface coverage.

Regional climate model assessment of the urban land-surface forcing over central Europe

NASA Astrophysics Data System (ADS)

Huszar, P.; Halenka, T.; Belda, M.; Zak, M.; Sindelarova, K.; Miksovsky, J.

2014-11-01

For the purpose of qualifying and quantifying the climate impact of cities and urban surfaces in general on climate of central Europe, the surface parameterization in regional climate model RegCM4 has been extended with the Single-layer Urban Canopy Model (SLUCM). A set of experiments was performed over the period of 2005-2009 for central Europe, either without considering urban surfaces or with the SLUCM treatment. Results show a statistically significant impact of urbanized surfaces on temperature (up to 1.5 K increase in summer) as well as on the boundary layer height (increases up to 50 m). Urbanization further influences surface wind with a winter decrease up to -0.6 m s-1, though both increases and decreases were detected in summer depending on the location relative to the cities and daytime (changes up to 0.3 m s-1). Urban surfaces significantly reduce the humidity over the surface. This impacts the simulated summer precipitation rate, showing a decrease over cities of up to -2 mm day-1. Significant temperature increases are simulated over higher altitudes as well, not only within the urban canopy layer. With the urban parameterization, the climate model better describes the diurnal temperature variation, reducing the cold afternoon and evening bias of RegCM4. Sensitivity experiments were carried out to quantify the response of the meteorological conditions to changes in the parameters specific to the urban environment, such as street width, building height, albedo of the roofs and anthropogenic heat release. The results proved to be rather robust and the choice of the key SLUCM parameters impacts them only slightly (mainly temperature, boundary layer height and wind velocity). Statistically significant impacts are modelled not only over large urbanized areas, but the influence of the cities is also evident over rural areas without major urban surfaces. It is shown that this is the result of the combined effect of the distant influence of the cities and the influence of the minor local urban surface coverage.

An overview of 2016 WISE Urban Summer Observation Campaign (WUSOC 2016) in the Seoul metropolitan area of South Korea

NASA Astrophysics Data System (ADS)

Jung, Jae-Won; Kim, Sang-Woo; Shim, Jae-Kwan; Kwak, Kyung-Hwan

2017-04-01

The Weather Information Service Engine (WISE), launched project of the Korea Meteorological Administration (KMA), aims to operate the urban meteorological observation network from 2012 to 2019 and to test and operate the application weather service (e.g., flash flood, road weather, city ecology, city microclimate, dispersion of hazardous substance etc.) in 2019 through the development of Advanced Storm-scale Analysis Prediction System(ASAPS) for the production of storm-scale hazard weather monitoring and prediction system. The WISE institute has completed construction of 31 urban meteorological observation cities in Seoul metropolitan area and has built a real-time test operation and verification system by improving the ASAPS that produces 1 km and 6 hour forecast information based on the 5 km forecast information of KMA. Field measurements of 2016 WISE Urban Summer Observation Campaign (WUSOC 2016) was conducted in the Seoul metropolitan area of South Korea from August 22 to October 14, 2016. Involving over 70 researchers from more than 12 environmental and atmospheric science research groups in South Korea, WUSOC2016 focused on special observations, severe rain storm observations using mobile observation car and radiosonde, wind profile observations using Wind Doppler Lidar and radiosonde, etc., around the Seoul metropolitan area. WUSOC2016 purpose at data quality control, accuracy verification, usability check, and quality improvement of ASAPS at observation stations constructed in WISE. In addition, we intend to contribute to the activation of urban fusion weather research and risk weather research through joint observation and data sharing.

Characterizing near-road air pollution using local-scale emission and dispersion models and validation against in-situ measurements

NASA Astrophysics Data System (ADS)

Wang, An; Fallah-Shorshani, Masoud; Xu, Junshi; Hatzopoulou, Marianne

2016-10-01

Near-road concentrations of nitrogen dioxide (NO2), a known marker of traffic-related air pollution, were simulated along a busy urban corridor in Montreal, Quebec using a combination of microscopic traffic simulation, instantaneous emission modeling, and air pollution dispersion. In order to calibrate and validate the model, a data collection campaign was designed. For this purpose, measurements of NO2 were conducted mid-block along four segments of the corridor throughout a four-week campaign conducted between March and April 2015. The four segments were chosen to be consecutive and yet exhibiting variability in road configuration and built environment characteristics. Roadside NO2 measurements were also paired with on-site and fixed-station meteorological data. In addition, traffic volumes, composition, and routing decisions were collected using video-cameras located at upstream and downstream intersections. Dispersion of simulated emissions was conducted for eight time slots and under a range of meteorological conditions using three different models with vastly different dispersion algorithms (OSPM, CALINE 4, and SIRANE). The three models exhibited poor correlation with near-road NO2 concentrations and were better able to simulate average concentrations occurring along the roadways rather than the range of concentrations measured under diverse meteorological and traffic conditions. As hypothesized, the model SIRANE that can handle a street canyon configuration was the most sensitive to the built environment especially to the presence of tall buildings around the road. In contrast, CALINE exhibited the lowest sensitivity to the built environment.

A physically based analytical spatial air temperature and humidity model

NASA Astrophysics Data System (ADS)

Yang, Yang; Endreny, Theodore A.; Nowak, David J.

2013-09-01

Spatial variation of urban surface air temperature and humidity influences human thermal comfort, the settling rate of atmospheric pollutants, and plant physiology and growth. Given the lack of observations, we developed a Physically based Analytical Spatial Air Temperature and Humidity (PASATH) model. The PASATH model calculates spatial solar radiation and heat storage based on semiempirical functions and generates spatially distributed estimates based on inputs of topography, land cover, and the weather data measured at a reference site. The model assumes that for all grids under the same mesoscale climate, grid air temperature and humidity are modified by local variation in absorbed solar radiation and the partitioning of sensible and latent heat. The model uses a reference grid site for time series meteorological data and the air temperature and humidity of any other grid can be obtained by solving the heat flux network equations. PASATH was coupled with the USDA iTree-Hydro water balance model to obtain evapotranspiration terms and run from 20 to 29 August 2010 at a 360 m by 360 m grid scale and hourly time step across a 285 km2 watershed including the urban area of Syracuse, NY. PASATH predictions were tested at nine urban weather stations representing variability in urban topography and land cover. The PASATH model predictive efficiency R2 ranged from 0.81 to 0.99 for air temperature and 0.77 to 0.97 for dew point temperature. PASATH is expected to have broad applications on environmental and ecological models.

Modeling regional/urban ozone and particulate matter in Beijing, China.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fu, J.S.; Streets, D.G.; Jang, C.J.

2009-01-15

This paper examines Beijing air quality in the winter and summer of 2001 using an integrated air quality modeling system (Fifth Generation Mesoscale Meteorological Model (MM5)/Community Multiscale Air Quality (CMAQ)) in nested mode. The National Aeronautics and Space Administration (NASA) Transport and Chemical Evolution over the Pacific (TRACE-P) emission inventory is used in the 36- (East Asia), 12- (East China), and 4-km (greater Beijing area) domains. Furthermore, we develop a local Beijing emission inventory that is used in the 4-km domain. We also construct a corroborated mapping of chemical species between the TRACE-P inventory and the Carbon Bond IV (CB-IV)more » chemical mechanism before the integrated modeling system is applied to study ozone (O{sub 3}) and particulate matter (PM) in Beijing. Meteorological data for the integrated modeling runs are extracted from MM5. Model results show O{sub 3} hourly concentrations in the range of 80-159 parts per billion (ppb) during summer in the urban areas and up to 189 ppb downwind of the city. High fine PM (PM2.5) concentrations (monthly average of 75 {mu}g.m{sup -3} in summer and 150 {mu}g.m{sup -3} in winter) are simulated over the metropolitan and down-wind areas with significant secondary constituents. Major sources of particulates were biomass burning, coal combustion and industry. A comparison against available O{sub 3} and PM measurement data in Beijing is described. We recommend refinements to the developed local Beijing emission inventory to improve the simulation of Beijing's air quality. The 4-km modeling configuration is also recommended for the development of air pollution control strategies. 31 refs., 5 figs., 3 tabs.« less

Application of a Three-Layer Photochemical Box Model in an Athens Street Canyon.

PubMed

Proyou, Athena G; Ziomas, Loannis C; Stathopoulos, Antony

1998-05-01

The aim of this paper is to show that a photochemical box model could describe the air pollution diurnal profiles within a typical street canyon in the city of Athens. As sophisticated three-dimensional dispersion models are computationally expensive and they cannot serve to simulate pollution levels in the scale of an urban street canyon, a suitably modified three-layer photochemical box model was applied. A street canyon of Athens with heavy traffic was chosen to apply the aforementioned model. The model was used to calculate pollutant concentrations during two days with meteorological conditions favoring pollutant accumulation. Road traffic emissions were calculated based on existing traffic load measurements. Meteorological data, as well as various pollutant concentrations, in order to compare with the model results, were provided by available measurements. The calculated concentrations were found to be in good agreement with measured concentration levels and show that, when traffic load and traffic composition data are available, this model can be used to predict pollution episodes. It is noteworthy that high concentrations persisted, even after additional traffic restriction measures were taken on the second day because of the high pollution levels.

Reassessment of urbanization effect on surface air temperature trends at an urban station of North China

NASA Astrophysics Data System (ADS)

Bian, Tao; Ren, Guoyu

2017-11-01

Based on a homogenized data set of monthly mean temperature, minimum temperature, and maximum temperature at Shijiazhuang City Meteorological Station (Shijiazhuang station) and four rural meteorological stations selected applying a more sophisticated methodology, we reanalyzed the urbanization effects on annual, seasonal, and monthly mean surface air temperature (SAT) trends for updated time period 1960-2012 at the typical urban station in North China. The results showed that (1) urbanization effects on the long-term trends of annual mean SAT, minimum SAT, and diurnal temperature range (DTR) in the last 53 years reached 0.25, 0.47, and - 0.50 °C/decade, respectively, all statistically significant at the 0.001 confidence level, with the contributions from urbanization effects to the overall long-term trends reaching 67.8, 78.6, and 100%, respectively; (2) the urbanization effects on the trends of seasonal mean SAT, minimum SAT, and DTR were also large and statistically highly significant. Except for November and December, the urbanization effects on monthly mean SAT, minimum SAT, and DTR were also all statistically significant at the 0.05 confidence level; and (3) the annual, seasonal, and monthly mean maximum SAT series at the urban station registered a generally weaker and non-significant urbanization effect. The updated analysis evidenced that our previous work for this same urban station had underestimated the urbanization effect and its contribution to the overall changes in the SAT series. Many similar urban stations were being included in the current national and regional SAT data sets, and the results of this paper further indicated the importance and urgency for paying more attention to the urbanization bias in the monitoring and detection of global and regional SAT change based on the data sets.

Vertical Ozone Concentration Profiles in the Middle East: WRF-Chem Predictions vs. Balloon Measurements

NASA Astrophysics Data System (ADS)

Fountoukis, C.; Ayoub, M.; Ackermann, L.; Gladich, I.; Hoehn, R.

2017-12-01

The greater Middle Eastern area is made up by more than 20 countries with over 400 million inhabitants. Due to extensive land conversion, intense industrialization and rapid urban population growth in recent years, the region's air quality is changing. High ozone levels affected by free tropospheric subsidence, long range transport and local production in large metropolitan areas of the region are of major concern. In this study we analyze data from i) continuously (24/7) operated ground monitoring stations, and ii) an ozonesonde station, operated in Doha by the Qatar Environment and Energy Research Institute coupled with simulations using a three-dimensional regional air quality model (WRF-Chem). Ozonesondes were launched at 1300 LT (1000 UTC) weekly during a summertime month (August 2015) representative of extremely hot and humid atmospheric conditions and a wintertime period (January/February 2016) of cool and dry conditions in the area. This is the first application of WRF-Chem in the Middle East focusing on vertical ozone concentrations on the lower troposphere (0 - 6 km) combined with high frequency vertical measurement (balloon) data. A triple nested model configuration has been selected with high spatial resolution over the domain of interest (2 × 2 km2). We examine different meteorological regimes and test the sensitivity of model predictions to planetary boundary layer parameterizations. Comparison of model predictions against observations show high correlation coefficients and encouragingly low biases in all meteorological variables. During wintertime, ozone is overall well predicted (Fractional Bias = -0.1) while the summertime comparison is more challenging. We suggest that the YSU scheme is more representative of the region and should be the scheme of choice in future WRF-Chem applications in the Middle East. Furthermore, we highlight the importance of revising the available anthropogenic emission inventory to account rapidly-changing urban environments of the Middle East. Results from the development of a new traffic-emissions inventory for urban environments will be discussed.

The impacts of urban surface characteristics on radiation balance and meteorological variables in the boundary layer around Beijing in summertime

NASA Astrophysics Data System (ADS)

Liu, Ruiting; Han, Zhiwei; Wu, Jian; Hu, Yonghong; Li, Jiawei

2017-11-01

In this study, some key geometric and thermal parameters derived from recent field and satellite observations in Beijing were collected and incorporated into WRF-UCM (Weather Research and Forecasting) model instead of previous default ones. A series of sensitivity model simulations were conducted to investigate the influences of these parameters on radiation balance, meteorological variables, turbulence kinetic energy (TKE), as well as planetary boundary layer height (PBLH) in regions around Beijing in summer 2014. Model validation demonstrated that the updated parameters represented urban surface characteristics more realistically and the simulations of meteorological variables were evidently improved to be closer to observations than the default parameters. The increase in building height tended to increase and slightly decrease surface air temperature at 2 m (T2) at night and around noon, respectively, and to reduce wind speed at 10 m (WS10) through a day. The increase in road width led to significant decreases in T2 and WS10 through the whole day, with the maximum changes in early morning and in evening, respectively. Both lower surface albedo and inclusion of anthropogenic heat (AH) resulted in increases in T2 and WS10 over the day, with stronger influence from AH. The vertical extension of the impact of urban surface parameters was mainly confined within 300 m at night and reached as high as 1600 m during daytime. The increase in building height tended to increase TKE and PBLH and the TKE increase was larger at night than during daytime due to enhancements of both mechanical and buoyant productions. The increase in road width generally reduced TKE and PBLH except for a few hours in the afternoon. The lower surface albedo and the presence of AH consistently resulted in increases of TKE and PBLH through both day and night. The increase in building height induced a slight divergence by day and a notable convergence at night, whereas the increase in road width led to a remarkable divergence through the entire day. Both AH and lower surface albedo induced a wind convergence over the day, which tended to strengthen nighttime mountain downslope wind and daytime southerly wind to the south of Beijing, but to weaken daytime upslope wind in mountain areas.

Modeling Atmospheric Transport for Greenhouse Gas Observations within the Urban Dome

NASA Astrophysics Data System (ADS)

Nehrkorn, T.; Sargent, M. R.; Wofsy, S. C.

2016-12-01

Observations of CO2, CH4, and other greenhouse gases (GHGs) within the urban dome of major cities generally show large enhancements over background values, and large sensitivity to surface fluxes (as measured by the footprints computed by Lagrangian Particle Dispersion Models, LPDMs) within the urban dome. However, their use in top-down inversion studies to constrain urban emission estimates is complicated by difficulties in proper modeling of the atmospheric transport. We are conducting experiments with the Weather Research and Forecast model (WRF) coupled to the STILT LPDM to improve model simulation of atmospheric transport on spatial scales of a few km in urban domains, because errors in transport on short time/space scales are amplified by the patchiness of GHG emissions and may engender systematic errors of simulated concentrations.We are evaluating the quality of the meteorological simulations from model configurations with different resolutions and PBL packages, using both standard and non-standard (Lidar PBL height and ACARS aircraft profile) observations. To take into account the effect of building scale eddies for observations located on top of buildings, we are modifying the basic STILT algorithm for the computation of footprints by replacing the nominal receptor height by an effective sampling height. In addition, the footprint computations for near-field emissions make use of the vertical particle spread within the LPDM to arrive at a more appropriate estimate of mixing heights in the immediate vicinity of receptors. We present the effect of these and similar modifications on simulated concentrations and their level of agreement with observed values.

Changes in regional meteorology induced by anthropogenic heat and their impacts on air quality in South China

NASA Astrophysics Data System (ADS)

Xie, Min; Zhu, Kuanguang; Wang, Tijian; Feng, Wen; Gao, Da; Li, Mengmeng; Li, Shu; Zhuang, Bingliang; Han, Yong; Chen, Pulong; Liao, Jingbiao

2016-12-01

Anthropogenic heat (AH) emissions from human activities can change the urban circulation and thereby affect the air pollution in and around cities. Based on statistic data, the spatial distribution of AH flux in South China is estimated. With the aid of the Weather Research and Forecasting model coupled with Chemistry (WRF/Chem), in which the AH parameterization is developed to incorporate the gridded AH emissions with temporal variation, simulations for January and July in 2014 are performed over South China. By analyzing the differences between the simulations with and without adding AH, the impact of AH on regional meteorology and air quality is quantified. The results show that the regional annual mean AH fluxes over South China are only 0.87 W m-2, but the values for the urban areas of the Pearl River Delta (PRD) region can be close to 60 W m-2. These AH emissions can significantly change the urban heat island and urban-breeze circulations in big cities. In the PRD city cluster, 2 m air temperature rises by 1.1° in January and over 0.5° in July, the planetary boundary layer height (PBLH) increases by 120 m in January and 90 m in July, 10 m wind speed is intensified to over 0.35 m s-1 in January and 0.3 m s-1 in July, and accumulative precipitation is enhanced by 20-40 % in July. These changes in meteorological conditions can significantly impact the spatial and vertical distributions of air pollutants. Due to the increases in PBLH, surface wind speed and upward vertical movement, the concentrations of primary air pollutants decrease near the surface and increase in the upper levels. But the vertical changes in O3 concentrations show the different patterns in different seasons. The surface O3 concentrations in big cities increase with maximum values of over 2.5 ppb in January, while O3 is reduced at the lower layers and increases at the upper layers above some megacities in July. This phenomenon can be attributed to the fact that chemical effects can play a significant role in O3 changes over South China in winter, while the vertical movement can be the dominant effect in some big cities in summer. Adding the gridded AH emissions can better describe the heterogeneous impacts of AH on regional meteorology and air quality, suggesting that more studies on AH should be carried out in climate and air quality assessments.

Development of a multi-ensemble Prediction Model for China

NASA Astrophysics Data System (ADS)

Brasseur, G. P.; Bouarar, I.; Petersen, A. K.

2016-12-01

As part of the EU-sponsored Panda and MarcoPolo Projects, a multi-model prediction system including 7 models has been developed. Most regional models use global air quality predictions provided by the Copernicus Atmospheric Monitoring Service and downscale the forecast at relatively high spatial resolution in eastern China. The paper will describe the forecast system and show examples of forecasts produced for several Chinese urban areas and displayed on a web site developed by the Dutch Meteorological service. A discussion on the accuracy of the predictions based on a detailed validation process using surface measurements from the Chinese monitoring network will be presented.

Chimney Perching Behavior in Birds: A Practical Urban Field Study Investigating the Relationship between Biology and Meteorology.

ERIC Educational Resources Information Center

Stamm, Alfred J.; And Others

1993-01-01

The study of starlings in the urban environment integrates nervous regulation, the senses, and animal behavior, while also providing an excellent example of how the biology of an animal is related to the demands of the physical environment. (PR)

Sea-town interactions over Marseille: 3D urban boundary layer and thermodynamic fields near the surface

NASA Astrophysics Data System (ADS)

Lemonsu, A.; Pigeon, G.; Masson, V.; Moppert, C.

2006-02-01

3D numerical simulations with the Meso-NH atmospheric model including the Town Energy Balance urban parameterization, are conducted over the south-east of France and the one million inhabitants city of Marseille in the frameworks of the ESCOMPTE-UBL program. The geographic situation of the area is relatively complex, because of the proximity of the Mediterranean Sea and the presence of numerous massifs, inducing complex meteorological flows. The present work is focused on six days of the campaign, characterized by the development of strong summer sea-breeze circulations. A complete evaluation of the model is initially realized at both regional- and city-scales, by using the large available database. The regional evaluation shows a good behavior of the model, during the six days of simulation, either for the parameters near the surface or for the vertical profiles describing the structure of the atmosphere. The urban-scale evaluation indicates that the fine structure of the horizontal fields of air temperature above the city is correctly simulated by the model. A specific attention is then pointed to the 250-m horizontal resolution outputs, focused on the Marseille area, for two days of the campaign. From the study of the vertical structure of the Urban Boundary Layer and the thermodynamic fields near the surface, one underscores the important differences due to the regional and local flows, and the complex interactions that occur between the urban effects and the effects of sea breezes.

Urban pavement surface temperature. Comparison of numerical and statistical approach

NASA Astrophysics Data System (ADS)

Marchetti, Mario; Khalifa, Abderrahmen; Bues, Michel; Bouilloud, Ludovic; Martin, Eric; Chancibaut, Katia

2015-04-01

The forecast of pavement surface temperature is very specific in the context of urban winter maintenance. to manage snow plowing and salting of roads. Such forecast mainly relies on numerical models based on a description of the energy balance between the atmosphere, the buildings and the pavement, with a canyon configuration. Nevertheless, there is a specific need in the physical description and the numerical implementation of the traffic in the energy flux balance. This traffic was originally considered as a constant. Many changes were performed in a numerical model to describe as accurately as possible the traffic effects on this urban energy balance, such as tires friction, pavement-air exchange coefficient, and infrared flux neat balance. Some experiments based on infrared thermography and radiometry were then conducted to quantify the effect fo traffic on urban pavement surface. Based on meteorological data, corresponding pavement temperature forecast were calculated and were compared with fiels measurements. Results indicated a good agreement between the forecast from the numerical model based on this energy balance approach. A complementary forecast approach based on principal component analysis (PCA) and partial least-square regression (PLS) was also developed, with data from thermal mapping usng infrared radiometry. The forecast of pavement surface temperature with air temperature was obtained in the specific case of urban configurtation, and considering traffic into measurements used for the statistical analysis. A comparison between results from the numerical model based on energy balance, and PCA/PLS was then conducted, indicating the advantages and limits of each approach.

Modeling carbon emissions from urban traffic system using mobile monitoring.

PubMed

Sun, Daniel Jian; Zhang, Ying; Xue, Rui; Zhang, Yi

2017-12-01

Comprehensive analyses of urban traffic carbon emissions are critical in achieving low-carbon transportation. This paper started from the architecture design of a carbon emission mobile monitoring system using multiple sets of equipment and collected the corresponding data about traffic flow, meteorological conditions, vehicular carbon emissions and driving characteristics on typical roads in Shanghai and Wuxi, Jiangsu province. Based on these data, the emission model MOVES was calibrated and used with various sensitivity and correlation evaluation indices to analyze the traffic carbon emissions at microscopic, mesoscopic and macroscopic levels, respectively. The major factors that influence urban traffic carbon emissions were investigated, so that emission factors of CO, CO 2 and HC were calculated by taking representative passenger cars as a case study. As a result, the urban traffic carbon emissions were assessed quantitatively, and the total amounts of CO, CO 2 and HC emission from passenger cars in Shanghai were estimated as 76.95kt, 8271.91kt, and 2.13kt, respectively. Arterial roads were found as the primary line source, accounting for 50.49% carbon emissions. In additional to the overall major factors identified, the mobile monitoring system and carbon emission quantification method proposed in this study are of rather guiding significance for the further urban low-carbon transportation development. Copyright © 2017 Elsevier B.V. All rights reserved.

Relationships between Changes in Urban Characteristics and Air Quality in East Asia from 2000 to 2010

PubMed Central

Larkin, Andrew; van Donkelaar, Aaron; Geddes, Jeffrey A.; Martin, Randall V.; Hystad, Perry

2017-01-01

Characteristics of urban areas, such as density and compactness, are associated with local air pollution concentrations. The potential for altering air pollution through changing urban characteristics, however, is less certain, especially for expanding cities within the developing world. We examined changes in urban characteristics from 2000 to 2010 for 830 cities in East Asia to evaluate associations with changes in nitrogen dioxide (NO2) and fine particulate matter (PM2.5) air pollution. Urban areas were stratified by population size into small (100,000–250,000), medium, (250,000–1,000,000) and large (>1,000,000). Multivariate regression models including urban baseline characteristics, meteorological variables, and change in urban characteristics explained 37%, 49%, and 54% of the change in NO2 and 29%, 34%, and 37% of the change in PM2.5 for small, medium and large cities, respectively. Change in lights at night strongly predicted change in NO2 and PM2.5, while urban area expansion was strongly associated with NO2 but not PM2.5. Important differences between changes in urban characteristics and pollutant levels were observed by city size, especially NO2. Overall, changes in urban characteristics had a greater impact on NO2 and PM2.5 change than baseline characteristics, suggesting urban design and land use policies can have substantial impacts on local air pollution levels. PMID:27442110

Performance evaluation of air quality models for predicting PM10 and PM2.5 concentrations at urban traffic intersection during winter period.

PubMed

Gokhale, Sharad; Raokhande, Namita

2008-05-01

There are several models that can be used to evaluate roadside air quality. The comparison of the operational performance of different models pertinent to local conditions is desirable so that the model that performs best can be identified. Three air quality models, namely the 'modified General Finite Line Source Model' (M-GFLSM) of particulates, the 'California Line Source' (CALINE3) model, and the 'California Line Source for Queuing & Hot Spot Calculations' (CAL3QHC) model have been identified for evaluating the air quality at one of the busiest traffic intersections in the city of Guwahati. These models have been evaluated statistically with the vehicle-derived airborne particulate mass emissions in two sizes, i.e. PM10 and PM2.5, the prevailing meteorology and the temporal distribution of the measured daily average PM10 and PM2.5 concentrations in wintertime. The study has shown that the CAL3QHC model would make better predictions compared to other models for varied meteorology and traffic conditions. The detailed study reveals that the agreements between the measured and the modeled PM10 and PM2.5 concentrations have been reasonably good for CALINE3 and CAL3QHC models. Further detailed analysis shows that the CAL3QHC model performed well compared to the CALINE3. The monthly performance measures have also led to the similar results. These two models have also outperformed for a class of wind speed velocities except for low winds (<1 m s(-1)), for which, the M-GFLSM model has shown the tendency of better performance for PM10. Nevertheless, the CAL3QHC model has outperformed for both the particulate sizes and for all the wind classes, which therefore can be optional for air quality assessment at urban traffic intersections.

Air-Quality and Climate Coupling in High Resolution for Urban Heat Island Study

NASA Astrophysics Data System (ADS)

Halenka, T.; Huszar, P.; Belda, M.

2012-04-01

Recent studies show considerable effect of atmospheric chemistry and aerosols on climate on regional and local scale. For the purpose of qualifying and quantifying the magnitude of climate forcing due to atmospheric chemistry/aerosols on regional scale and climate change effects on air-quality the regional climate model RegCM and chemistry/aerosol model CAMx was coupled. Climate change impacts on air-quality have been studied in high resolution of 10km with interactive two-way coupling of the effects of air-quality on climate. The experiments with the couple were performed for EC FP7 project MEGAPOLI assessing the impact of the megacities and industrialized areas on climate. New experiments in high resolution are prepared andsimulated for Urban Heat Island studies within the OP Central Europe Project UHI. Meteorological fields generated by RCM drive CAMx transport, chemistry and a dry/wet deposition. A preprocessor utility was developed for transforming RegCM provided fields to CAMx input fields and format. There is critical issue of the emission inventories available for 10km resolution including the urban hot-spots, TNO emissions are adopted for the experiments. Sensitivity tests switching on/off urban areas emissions are analysed as well. The results for year 2005 are presented and discussed, interactive coupling is compared to study the potential of possible impact of urban air-pollution to the urban area climate.

Application of a photochemical grid model to milan metropolitan area

NASA Astrophysics Data System (ADS)

Silibello, C.; Calori, G.; Brusasca, G.; Catenacci, G.; Finzi, G.

High ozone levels are regularly reached during summer period in South-European urban areas, calling for careful design of primary pollutants emission reduction strategies. In this perspective the CALGRID modelling system has been applied to Milan metropolitan area, located in the Po Valley, the most industrialised and populated area in Italy. For the first modelling exercise, a simulation domain of 100×100 km 2 has been considered and a summer period, characterised by high photochemical activity, has been selected. Hourly emissions have been derived by spatially and temporally disaggregating national inventories data, while standard upper-air and ground-based meteorological data have been used as input to the CALMET pre-processor. A careful analysis of simulation results versus local network monitoring data has revealed some critical points, related to both modelling assumptions and practical data availability. A satisfactory reproduction of daytime ozone behaviour has been, in fact, accomplished, both in urban and suburban sites, while nighttime primary pollutants accumulations and consequent ozone consumption simulated by the model have not found correspondence in the measurements. Nitrogen dioxide has been also successfully modelled, mostly in city surroundings, whereas higher discrepancies have been found in some urban stations. Possible explanations of these facts are discussed in the paper, giving an insight for further work.

Basic analysis of climate and urban bioclimate of Dar es Salaam, Tanzania

NASA Astrophysics Data System (ADS)

Ndetto, Emmanuel L.; Matzarakis, Andreas

2013-10-01

Better understanding of urban microclimate and bioclimate of any city is imperative today when the world is constrained by both urbanisation and global climate change. Urbanisation generally triggers changes in land cover and hence influencing the urban local climate. Dar es Salaam city in Tanzania is one of the fast growing cities. Assessment of its urban climate and the human biometeorological conditions was done using the easily available synoptic meteorological data covering the period 2001-2011. In particular, the physiologically equivalent temperature (PET) was calculated using the RayMan software and results reveal that the afternoon period from December to February (DJF season) is relatively the most thermal stressful period to human beings in Dar es Salaam where PET values of above 35 °C were found. Additionally, the diurnal cycle of the individual meteorological elements that influence the PET index were analysed and found that air temperature of 30-35 °C dominate the afternoon period from 12:00 to 15:00 hours local standard time at about 60 % of occurrence. The current results, though considered as preliminary to the ongoing urban climate study in the city, provide an insight on how urban climate research is of significant importance in providing useful climatic information for ensuring quality of life and wellbeing of city dwellers.

Systematic flood modelling to support flood-proof urban design

NASA Astrophysics Data System (ADS)

Bruwier, Martin; Mustafa, Ahmed; Aliaga, Daniel; Archambeau, Pierre; Erpicum, Sébastien; Nishida, Gen; Zhang, Xiaowei; Pirotton, Michel; Teller, Jacques; Dewals, Benjamin

2017-04-01

Urban flood risk is influenced by many factors such as hydro-meteorological drivers, existing drainage systems as well as vulnerability of population and assets. The urban fabric itself has also a complex influence on inundation flows. In this research, we performed a systematic analysis on how various characteristics of urban patterns control inundation flow within the urban area and upstream of it. An urban generator tool was used to generate over 2,250 synthetic urban networks of 1 km2. This tool is based on the procedural modelling presented by Parish and Müller (2001) which was adapted to generate a broader variety of urban networks. Nine input parameters were used to control the urban geometry. Three of them define the average length, orientation and curvature of the streets. Two orthogonal major roads, for which the width constitutes the fourth input parameter, work as constraints to generate the urban network. The width of secondary streets is given by the fifth input parameter. Each parcel generated by the street network based on a parcel mean area parameter can be either a park or a building parcel depending on the park ratio parameter. Three setback parameters constraint the exact location of the building whithin a building parcel. For each of synthetic urban network, detailed two-dimensional inundation maps were computed with a hydraulic model. The computational efficiency was enhanced by means of a porosity model. This enables the use of a coarser computational grid , while preserving information on the detailed geometry of the urban network (Sanders et al. 2008). These porosity parameters reflect not only the void fraction, which influences the storage capacity of the urban area, but also the influence of buildings on flow conveyance (dynamic effects). A sensitivity analysis was performed based on the inundation maps to highlight the respective impact of each input parameter characteristizing the urban networks. The findings of the study pinpoint which properties of urban networks have a major influence on urban inundation flow, enabling better informed flood-proof urban design. References: Parish, Y. I. H., Muller, P. 2001. Procedural modeling of cities. SIGGRAPH, pp. 301—308. Sanders, B.F., Schubert, J.E., Gallegos, H.A., 2008. Integral formulation of shallow-water equations with anisotropic porosity for urban flood modeling. Journal of Hydrology 362, 19-38. Acknowledgements: The research was funded through the ARC grant for Concerted Research Actions, financed by the Wallonia-Brussels Federation.

Wetlands with greater degree of urbanization improve PM2.5 removal efficiency.

PubMed

Liu, Jiakai; Yan, Guoxin; Wu, Yanan; Wang, Yu; Zhang, Zhenming; Zhang, Mingxiang

2018-09-01

In recent decades, China has experienced both rapid urbanization and heavy air pollution and the rapid urbanization trend would be continue in the next decade. Wetlands have been shown to be efficient in particle removal, primarily through dry deposition and leaf accumulation. Thus, a more comprehensive understanding of PM2.5 removal by wetlands during urbanization processes could inform urban planning. In the current study, three wetland plots, Cuihu Lake Park (CL), Summer Palace (SP), and Olympic Park (OP), were selected as low, medium, and highly degrees of urbanization site respectively based on the proportions of building and traffic district areas to compare the removal efficiencies. Results show the average dry deposition velocity in OP was significantly higher than CL and SP. Dry deposition is mainly influenced by meteorological conditions. Buildings and other infrastructure make the meteorological conditions conducive to deposition, resulting in higher wind velocity, higher temperature, and more intense turbulence between buildings. Variation in leaf accumulation was not statistically significant between the three plots, and plant species was the major factor affecting the amount of accumulation. The dry deposition contribution to particle removal increases with degree of urbanization. The average dry deposition accounted for 39.74%, 52.55%, and 62.75% at low, middle and high level respectively. Therefore, Wetlands with greater degree of urbanization improve PM2.5 removal efficiency primarily by accelerating the dry deposition process. The result emphasizes the importance of wetlands in particle removal in highly urbanized areas and thus more wetlands should be preserved and/or created during urban expansion. Copyright © 2018 Elsevier Ltd. All rights reserved.

The urban impact on the regional climate of Dresden

NASA Astrophysics Data System (ADS)

Sändig, B.; Renner, E.

2010-09-01

The principal objective of this research is to clarify the impact of urban elements such as buildings and streets on the regional climate and air quality in the framework of the BMBF-project "Regionales Klimaanpassungsprogramm f¨ur die Modellregion Dresden" (REGKLAM). Drawing on the example of Dresden this work explores how the presence of cities influences the atmospheric flow and the characteristics of the boundary layer. Persuing this target, an urban surface exchange parameterisation module (Martilli et al., 2002) was implemented in a high resolution version of the COSMO model, the forecast model of the German Weather Service (DWD). Using a mesoscale model for this regional climate study implies the advantage of embedding the focused area in a realistic large scale situation via downscaling by means of one way nesting and allows to simulate the urban impact for different IPCC-szenarios. The urban module is based on the assumption that a city could be represented by a bunch of "urban classes". Each urban class is characterised by specific properties such as typical street directions or probability of finding a building in a special height. Based on urban structure data of Dresden (vector shape-files containing the outlines of all buildings and the respective heights) an automated method of extracting the relevant geometrical input parameters for the urban module was developed. By means of this model setup we performed case studies, in which we investigate the interactions between the city structure and the meteorological variables with regard to special synoptical situations such as the Bohemian wind, a typical flow pattern of cold air, sourced from the Bohemian Basin, in the Elbe Valley, which acts then like a wind channel. Another focal point is formed by the investigation of different types of artificial cities ranging from densely builtup areas to suburban areas in order to illuminating the impact of the city type on the dynamical and thermal properties of the atmosphere.

Remote Sensing of Urban Thermal Landscape Characteristics and Their Affects on Local and Regional Meteorology and Air Quality: An Overview of NASA EOS-IDS Project Atlanta

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.; Estes, Maurice G., Jr.

1999-01-01

As an entity, the city is a manifestation of human "management" of the land. The act of city-building, however, drastically alters the biophysical environment, which ultimately, impacts local and regional land-atmosphere energy exchange processes. Because of the complexity of both the urban landscape and the attendant energy fluxes that result from urbanization, remote sensing offers the only real way to synoptically quantify these processes. One of the more important land-atmosphere fluxes that occurs over cities relates to the way that thermal energy is partitioned across the heterogeneous urban landscape. The individual land cover and surface material types that comprise the city, such as pavements and buildings, each have their own thermal energy regimes. As the collective urban landscape, the individual thermal energy responses from specific surfaces come together to form the urban heat island phenomena, which prevails as a dome of elevated air temperatures over cities. Although the urban heat island has been known to exist for well over 150 years, it is not understood how differences in thermal energy responses for land covers across the city interact to produce this phenomenon, or how the variability in thermal energy responses from different surface types drive its development. Additionally, it can be hypothesized that as cities grow in size through time, so do their urban heat islands. The interrelationships between urban sprawl and the respective growth of the urban heat island, however, have not been investigated. Moreover, little is known of the consequential effects of urban growth, land cover change, and the urban heat island as they impact local and regional meteorology and air quality.

Air quality assessment of Estarreja, an urban industrialized area, in a coastal region of Portugal.

PubMed

Figueiredo, M L; Monteiro, A; Lopes, M; Ferreira, J; Borrego, C

2013-07-01

Despite the increasing concern given to air quality in urban and industrial areas in recent years, particular emphasis on regulation, control, and reduction of air pollutant emissions is still necessary to fully characterize the chain emissions-air quality-exposure-dose-health effects, for specific sources. The Estarreja region was selected as a case study because it has one of the largest chemical industrial complexes in Portugal that has been recently expanded, together with a growing urban area with an interesting location in the Portuguese coastland and crossed by important road traffic and rail national networks. This work presents the first air quality assessment for the region concerning pollutant emissions and meteorological and air quality monitoring data analysis, over the period 2000-2009. This assessment also includes a detailed investigation and characterization of past air pollution episodes for the most problematic pollutants: ozone and PM10. The contribution of different emission sources and meteorological conditions to these episodes is investigated. The stagnant meteorological conditions associated with local emissions, namely industrial activity and road traffic, are the major contributors to the air quality degradation over the study region. A set of measures to improve air quality--regarding ozone and PM10 levels--is proposed as an air quality management strategy for the study region.

Introduction to Global Urban Climatology

NASA Astrophysics Data System (ADS)

Varquez, A. C. G.; Kanda, M.; Kawano, N.; Darmanto, N. S.; Dong, Y.

2016-12-01

Urban heat island (UHI) is a widely investigated phenomenon in the field of urban climate characterized by the warming of urban areas relative to its surrounding rural environs. Being able to understand the mechanism behind the UHI formation of a city and distinguish its impact from that of global climate change is indispensable when identifying adaptation and mitigation strategies. However, the lack of UHI studies many cities especially for developing countries makes it difficult to generalize the mechanism for UHI formation. Thus, there is an impending demand for studies that focus on the simultaneous analyses of UHI and its trends throughout the world. Hence, we propose a subfield of urban climatology, called "global urban climatology" (GUC), which mainly focuses on the uniform understanding of urban climates across all cities, globally. By using globally applicable methodologies to quantify and compare urban heat islands of cities with diverse backgrounds, including their geography, climate, socio-demography, and other factors, a universal understanding of the mechanisms underlying the formation of the phenomenon can be established. The implementation of GUC involves the use of globally acquired historical observation networks, gridded meteorological parameters from climate models, global geographic information system datasets; the construction of a distributed urban parameter database; and the development of techniques necessary to model the urban climate. Research under GUC can be categorized into three approaches. The collaborative approach (1st) relies on the collection of data from micro-scale experiments conducted worldwide with the aid or development of professional social networking platforms; the analytical approach (2nd) relies on the use of global weather station datasets and their corresponding objectively analysed global outputs; and the numerical approach (3rd) relies on the global estimation of high-resolution urban-representative parameters as inputs to global weather modelling. The GUC concept, the pathways through which GUC assessments can be undertaken, and current implementations are introduced. Acknowledgment: This research was supported by the Environment Research and Technology Development Fund (S-14) of the Ministry of the Environment, Japan.

In-vehicle exposures to particulate air pollution in Canadian metropolitan areas: the urban transportation exposure study.

PubMed

Weichenthal, Scott; Van Ryswyk, Keith; Kulka, Ryan; Sun, Liu; Wallace, Lance; Joseph, Lawrence

2015-01-06

Commuters may be exposed to increased levels of traffic-related air pollution owing to close proximity to traffic-emissions. We collected in-vehicle and roof-top air pollution measurements over 238 commutes in Montreal, Toronto, and Vancouver, Canada between 2010 and 2013. Voice recordings were used to collect real-time information on traffic density and the presence of diesel vehicles and multivariable linear regression models were used to estimate the impact of these factors on in-vehicle pollutant concentrations (and indoor/outdoor ratios) along with parameters for road type, land use, and meteorology. In-vehicle PM2.5 and NO2 concentrations consistently exceeded regional outdoor levels and each unit increase in the rate of encountering diesel vehicles (count/min) was associated with substantial increases (>100%) in in-vehicle concentrations of ultrafine particles (UFPs), black carbon, and PM2.5 as well as strong increases (>15%) in indoor/outdoor ratios. A model based on meteorology and the length of highway roads within a 500 m buffer explained 53% of the variation in in-vehicle UFPs; however, models for PM2.5 (R(2) = 0.24) and black carbon (R(2) = 0.30) did not perform as well. Our findings suggest that vehicle commuters experience increased exposure to air pollutants and that traffic characteristics, land use, road types, and meteorology are important determinants of these exposures.

Effects of income and urban form on urban NO2: global evidence from satellites.

PubMed

Bechle, Matthew J; Millet, Dylan B; Marshall, Julian D

2011-06-01

Urban air pollution is among the top 15 causes of death and disease worldwide, and a problem of growing importance with a majority of the global population living in cities. A important question for sustainable development is to what extent urban design can improve or degrade the environment and public health. We investigate relationships between satellite-derived estimates of nitrogen dioxide concentration (NO(2), a key component of urban air pollution) and urban form for 83 cities globally. We find a parsimonious yet powerful relationship (model R(2) = 0.63), using as predictors population, income, urban contiguity, and meteorology. Cities with highly contiguous built-up areas have, on average, lower urban NO(2) concentrations (a one standard deviation increase in contiguity is associated with a 24% decrease in average NO(2) concentration). More-populous cities tend to have worse air quality, but the increase in NO(2) associated with a population increase of 10% may be offset by a moderate increase (4%) in urban contiguity. Urban circularity ("compactness") is not a statistically significant predictor of NO(2) concentration. Although many factors contribute to urban air pollution, our findings suggest that antileapfrogging policies may improve air quality. We find that urban NO(2) levels vary nonlinearly with income (Gross Domestic Product), following an "environmental Kuznets curve"; we estimate that if high-income countries followed urban pollution-per-income trends observed for low-income countries, NO(2) concentrations in high-income cities would be ∼10× larger than observed levels.

Validation of a Fast-Response Urban Micrometeorological Model to Assess the Performance of Urban Heat Island Mitigation Strategies

NASA Astrophysics Data System (ADS)

Nadeau, D.; Girard, P.; Overby, M.; Pardyjak, E.; Stoll, R., II; Willemsen, P.; Bailey, B.; Parlange, M. B.

2015-12-01

Urban heat islands (UHI) are a real threat in many cities worldwide and mitigation measures have become a central component of urban planning strategies. Even within a city, causes of UHI vary from one neighborhood to another, mostly due the spatial variability in surface thermal properties, building geometry, anthropogenic heat flux releases and vegetation cover. As a result, the performance of UHI mitigation measures also varies in space. Hence, there is a need to develop a tool to quantify the efficiency of UHI mitigation measures at the neighborhood scale. The objective of this ongoing study is to validate the fast-response micrometeorological model QUIC EnvSim (QES). This model can provide all information required for UHI studies with a fine spatial resolution (up to 0.5m) and short computation time. QES combines QUIC, a CFD-based wind solver and dispersion model, and EnvSim, composed of a radiation model, a land-surface model and a turbulent transport model. Here, high-resolution (1 m) simulations are run over a subset of the École Polytechnique Fédérale de Lausanne (EPFL) campus including complex buildings, various surfaces properties and vegetation. For nearly five months in 2006-07, a dense network of meteorological observations (92 weather stations over 0.1 km2) was deployed over the campus and these unique data are used here as a validation dataset. We present validation results for different test cases (e.g., sunny vs cloudy days, different incoming wind speeds and directions) and explore the effect of a few UHI mitigation strategies on the spatial distribution of near-surface air temperatures. Preliminary results suggest that QES may be a valuable tool in decision-making regarding adaptation of urban planning to UHI.

Vertical PM10 Characteristics and their Relation with Tropospheric Meteorology over Hong Kong

NASA Astrophysics Data System (ADS)

Hei Tong, Cheuk

2016-04-01

Small particulates or PM10, those with aerodynamic diameters less than 10 mm, can cause long term impairment to human health as they can penetrate deep and deposit on the wall of the respiratory system. Hong Kong receives significant concentration of cross-boundary particulates but at the same time produce domestic pollutants which altogether contribute to the total pollution problem. Recent research interest is paying more attention on the vertical characteristic of PM in the lower atmosphere as possible correlations exist along different altitude. Besides, there exists potential relationship between PM concentration aloft and the high-level weather condition. Yet, most studies focus only up to around 200 meters above sea level due to the proposed significance and the lack of technology. Undoubtedly, this is not enough in investigating the relation between vertical atmospheric profile and PM vertical characteristics. New technology development has allowed measuring PM concentration along the vertical atmospheric profile up to tropopause. This measurement relies on the Atmospheric Light Detection and Ranging (LiDAR) which operates using the radar principle to detect Rayleigh and Mie scattering from atmospheric gas and aerosols. The research involves (1) study of the seasonal vertical PM10 characteristics in five studying site of Hong Kong covering urban, suburban and rural area; (2) the relationship of the PM10 characteristics with meteorological parameters; (3) the vertical PM10 characteristics under the approach of tropical cyclones. A portable Micro Pulse Lidar (MPL) is adopted to collect PM data aloft while surface PM data is collected from ground stations. High-level meteorology data is received from Hong Kong Observatory. Statistical analyses are operated to investigate the correlation between weather conditions and PM concentration along the vertical profile. The research study is divided in phrases. The ultimate goal of the study is to develop models simulating high-level PM concentration under different meteorological conditions and predict the impacts under global and urban climate change. Keywords: PM10; High level meteorology; Seasonal variations; Tropical cyclone; Hong Kong; LiDAR

Urban air pollution and meteorological factors affect emergency department visits of elderly patients with chronic obstructive pulmonary disease in Taiwan.

PubMed

Ding, Pei-Hsiou; Wang, Gen-Shuh; Guo, Yue-Leon; Chang, Shuenn-Chin; Wan, Gwo-Hwa

2017-05-01

Both air pollution and meteorological factors in metropolitan areas increased emergency department (ED) visits from people with chronic obstructive pulmonary disease (COPD). Few studies investigated the associations between air pollution, meteorological factors, and COPD-related health disorders in Asian countries. This study aimed to investigate the relationship between the environmental factors and COPD-associated ED visits of susceptible elderly population in the largest Taiwanese metropolitan area (Taipei area, including Taipei city and New Taipei city) between 2000 and 2013. Data of air pollutant concentrations (PM 10 , PM 2.5 , O 3 , SO 2 , NO 2 and CO), meteorological factors (daily temperature, relative humidity and air pressure), and daily COPD-associated ED visits were collected from Taiwan Environmental Protection Administration air monitoring stations, Central Weather Bureau stations, and the Taiwan National Health Insurance database in Taipei area. We used a case-crossover study design and conditional logistic regression models with odds ratios (ORs), and 95% confidence intervals (CIs) for evaluating the associations between the environmental factors and COPD-associated ED visits. Analyses showed that PM 2.5 , O 3 , and SO 2 had significantly greater lag effects (the lag was 4 days for PM 2.5 , and 5 days for O 3 and SO 2 ) on COPD-associated ED visits of the elderly population (65-79 years old). In warmer days, a significantly greater effect on elderly COPD-associated ED visits was estimated for PM 2.5 with coexistence of O 3 . Additionally, either O 3 or SO 2 combined with other air pollutants increased the risk of elderly COPD-associated ED visits in the days of high relative humidity and air pressure difference, respectively. This study showed that joint effect of urban air pollution and meteorological factors contributed to the COPD-associated ED visits of the susceptible elderly population in the largest metropolitan area in Taiwan. Government authorities should review existing air pollution policies, and strengthen health education propaganda to ensure the health of the susceptible elderly population. Copyright © 2017 Elsevier Ltd. All rights reserved.

CONTINUOUS MEASUREMENT OF FINE AND ULTRAFINE PARTICULATE MATTER, CRITERIA POLLUTANTS AND METEOROLOGICAL CONDITIONS IN URBAN EL PASO, TEXAS

EPA Science Inventory

Continuous measurements of aerosol size distributions were made in El Paso, TX, for a period in winter 1999. Size distribution measurements were performed at two urban locations in El Paso using two pairs of the scanning mobility particle sizer and the aerodynamic particle si...

Safety on Earth From MARSS

NASA Technical Reports Server (NTRS)

2002-01-01

ENSCO, Inc., developed the Meteorological and Atmospheric Real-time Safety Support (MARSS) system for real-time assessment of meteorological data displays and toxic material spills. MARSS also provides mock scenarios to guide preparations for emergencies involving meteorological hazards and toxic substances. Developed under a Small Business Innovation Research (SBIR) contract with Kennedy Space Center, MARSS was designed to measure how safe NASA and Air Force range safety personnel are while performing weather sensitive operations around launch pads. The system augments a ground operations safety plan that limits certain work operations to very specific weather conditions. It also provides toxic hazard prediction models to assist safety managers in planning for and reacting to releases of hazardous materials. MARSS can be used in agricultural, industrial, and scientific applications that require weather forecasts and predictions of toxic smoke movement. MARSS is also designed to protect urban areas, seaports, rail facilities, and airports from airborne releases of hazardous chemical substances. The system can integrate with local facility protection units and provide instant threat detection and assessment data that is reportable for local and national distribution.

How Socio-Environmental Factors Are Associated with Japanese Encephalitis in Shaanxi, China—A Bayesian Spatial Analysis

PubMed Central

Zhang, Shaobai; Hu, Wenbiao; Zhuang, Guihua

2018-01-01

Evidence indicated that socio-environmental factors were associated with occurrence of Japanese encephalitis (JE). This study explored the association of climate and socioeconomic factors with JE (2006–2014) in Shaanxi, China. JE data at the county level in Shaanxi were supplied by Shaanxi Center for Disease Control and Prevention. Population and socioeconomic data were obtained from the China Population Census in 2010 and statistical yearbooks. Meteorological data were acquired from the China Meteorological Administration. A Bayesian conditional autoregressive model was used to examine the association of meteorological and socioeconomic factors with JE. A total of 1197 JE cases were included in this study. Urbanization rate was inversely associated with JE incidence during the whole study period. Meteorological variables were significantly associated with JE incidence between 2012 and 2014. The excessive precipitation at lag of 1–2 months in the north of Shaanxi in June 2013 had an impact on the increase of local JE incidence. The spatial residual variations indicated that the whole study area had more stable risk (0.80–1.19 across all the counties) between 2012 and 2014 than earlier years. Public health interventions need to be implemented to reduce JE incidence, especially in rural areas and after extreme weather. PMID:29584661

DOE Office of Scientific and Technical Information (OSTI.GOV)

Glascoe, Lee; Gowardhan, Akshay; Lennox, Kristin

In the interest of promoting the international exchange of technical expertise, the US Department of Energy’s Office of Emergency Operations (NA-40) and the French Commissariat à l'Energie Atomique et aux énergies alternatives (CEA) requested that the National Atmospheric Release Advisory Center (NARAC) of Lawrence Livermore National Laboratory (LLNL) in Livermore, California host a joint table top exercise with experts in emergency management and atmospheric transport modeling. In this table top exercise, LLNL and CEA compared each other’s flow and dispersion models. The goal of the comparison is to facilitate the exchange of knowledge, capabilities, and practices, and to demonstrate themore » utility of modeling dispersal at different levels of computational fidelity. Two modeling approaches were examined, a regional scale modeling approach, appropriate for simple terrain and/or very large releases, and an urban scale modeling approach, appropriate for small releases in a city environment. This report is a summary of LLNL and CEA modeling efforts from this exercise. Two different types of LLNL and CEA models were employed in the analysis: urban-scale models (Aeolus CFD at LLNL/NARAC and Parallel- Micro-SWIFT-SPRAY, PMSS, at CEA) for analysis of a 5,000 Ci radiological release and Lagrangian Particle Dispersion Models (LODI at LLNL/NARAC and PSPRAY at CEA) for analysis of a much larger (500,000 Ci) regional radiological release. Two densely-populated urban locations were chosen: Chicago with its high-rise skyline and gridded street network and Paris with its more consistent, lower building height and complex unaligned street network. Each location was considered under early summer daytime and nighttime conditions. Different levels of fidelity were chosen for each scale: (1) lower fidelity mass-consistent diagnostic, intermediate fidelity Navier-Stokes RANS models, and higher fidelity Navier-Stokes LES for urban-scale analysis, and (2) lower-fidelity single-profile meteorology versus higher-fidelity three-dimensional gridded weather forecast for regional-scale analysis. Tradeoffs between computation time and the fidelity of the results are discussed for both scales. LES, for example, requires nearly 100 times more processor time than the mass-consistent diagnostic model or the RANS model, and seems better able to capture flow entrainment behind tall buildings. As anticipated, results obtained by LLNL and CEA at regional scale around Chicago and Paris look very similar in terms of both atmospheric dispersion of the radiological release and total effective dose. Both LLNL and CEA used the same meteorological data, Lagrangian particle dispersion models, and the same dose coefficients. LLNL and CEA urban-scale modeling results show consistent phenomenological behavior and predict similar impacted areas even though the detailed 3D flow patterns differ, particularly for the Chicago cases where differences in vertical entrainment behind tall buildings are particularly notable. Although RANS and LES (LLNL) models incorporate more detailed physics than do mass-consistent diagnostic flow models (CEA), it is not possible to reach definite conclusions about the prediction fidelity of the various models as experimental measurements were not available for comparison. Stronger conclusions about the relative performances of the models involved and evaluation of the tradeoffs involved in model simplification could be made with a systematic benchmarking of urban-scale modeling. This could be the purpose of a future US / French collaborative exercise.« less

Estimating regional spatial and temporal variability of PM(2.5) concentrations using satellite data, meteorology, and land use information.

PubMed

Liu, Yang; Paciorek, Christopher J; Koutrakis, Petros

2009-06-01

Studies of chronic health effects due to exposures to particulate matter with aerodynamic diameters

Dispersion modeling of accidental releases of toxic gases - utility for the fire brigades.

NASA Astrophysics Data System (ADS)

Stenzel, S.; Baumann-Stanzer, K.

2009-09-01

Several air dispersion models are available for prediction and simulation of the hazard areas associated with accidental releases of toxic gases. The most model packages (commercial or free of charge) include a chemical database, an intuitive graphical user interface (GUI) and automated graphical output for effective presentation of results. The models are designed especially for analyzing different accidental toxic release scenarios ("worst-case scenarios”), preparing emergency response plans and optimal countermeasures as well as for real-time risk assessment and management. The research project RETOMOD (reference scenarios calculations for toxic gas releases - model systems and their utility for the fire brigade) was conducted by the Central Institute for Meteorology and Geodynamics (ZAMG) in cooperation with the Viennese fire brigade, OMV Refining & Marketing GmbH and Synex Ries & Greßlehner GmbH. RETOMOD was funded by the KIRAS safety research program of the Austrian Ministry of Transport, Innovation and Technology (www.kiras.at). The main tasks of this project were 1. Sensitivity study and optimization of the meteorological input for modeling of the hazard areas (human exposure) during the accidental toxic releases. 2. Comparison of several model packages (based on reference scenarios) in order to estimate the utility for the fire brigades. For the purpose of our study the following models were tested and compared: ALOHA (Areal Location of Hazardous atmosphere, EPA), MEMPLEX (Keudel av-Technik GmbH), Trace (Safer System), Breeze (Trinity Consulting), SAM (Engineering office Lohmeyer). A set of reference scenarios for Chlorine, Ammoniac, Butane and Petrol were proceed, with the models above, in order to predict and estimate the human exposure during the event. Furthermore, the application of the observation-based analysis and forecasting system INCA, developed in the Central Institute for Meteorology and Geodynamics (ZAMG) in case of toxic release was investigated. INCA (Integrated Nowcasting through Comprehensive Analysis) data are calculated operationally with 1 km horizontal resolution and based on the weather forecast model ALADIN. The meteorological field's analysis with INCA include: Temperature, Humidity, Wind, Precipitation, Cloudiness and Global Radiation. In the frame of the project INCA data were compared with measurements from the meteorological observational network, conducted at traffic-near sites in Vienna. INCA analysis and very short term forecast fields (up to 6 hours) are found to be an advanced possibility to provide on-line meteorological input for the model package used by the fire brigade. Since the input requirements differ from model to model, and the outputs are based on unequal criteria for toxic area and exposure, a high degree of caution in the interpretation of the model results is required - especially in the case of slow wind speeds, stable atmospheric condition, and flow deflection by buildings in the urban area or by complex topography.

Urban airborne matter in central and southern Chile: Effects of meteorological conditions on fine and coarse particulate matter

NASA Astrophysics Data System (ADS)

Yáñez, Marco A.; Baettig, Ricardo; Cornejo, Jorge; Zamudio, Francisco; Guajardo, Jorge; Fica, Rodrigo

2017-07-01

Air pollution is one of the major global environmental problems affecting human health and life quality. Many cities of Chile are heavily polluted with PM2.5 and PM10, mainly in the cold season, and there is little understanding of how the variation in particle matter differs between cities and how this is affected by the meteorological conditions. The objective of this study was to assess the effect of meteorological variables on respirable particulate matter (PM) of the main cities in the central-south valley of Chile during the cold season (May to August) between 2014 and 2016. We used hourly PM2.5 and PMcoarse (PM10- PM2.5) information along with wind speed, temperature and relative humidity, and other variables derived from meteorological parameters. Generalized additive models (GAMs) were fitted for each of the eight cities selected, covering a latitudinal range of 929 km, from Santiago to Osorno. Great variation in PM was found between cities during the cold months, and that variation exhibited a marked latitudinal pattern. Overall, the more northerly cities tended to be less polluted in PM2.5 and more polluted in PMcoarse than the more southerly cities, and vice versa. The results show that other derived variables from meteorology were better related with PM than the use of traditional daily means. The main variables selected with regard to PM2.5 content were mean wind speed and minimum temperature (negative relationship). Otherwise, the main variables selected with regard to PMcoarse content were mean wind speed (negative), and the daily range in temperature (positive). Variables derived from relative humidity contributed differently to the models, having a higher effect on PMcoarse than PM2.5, and exhibiting both negative and positive effects. For the different cities the deviance explained by the GAMs ranged from 37.6 to 79.1% for PM2.5 and from 18.5 to 63.7% for PMcoarse. The percentage of deviance explained by the models for PM2.5 exhibited a latitudinal pattern, which was not observed in PMcoarse. This highlights the greater predictability of PM2.5 according to meteorological parameters in the cities to the south. Southern cities located spatially close to one another had similar patterns in both the selected variables for the models and the trends. The meteorological factor influencing the cities had a major impact on PM concentrations. The findings of this study may aid understanding of PM variation across the country, in the way of improving forecasting models.

Evaluation of regional and local atmospheric dispersion models for the analysis of traffic-related air pollution in urban areas

NASA Astrophysics Data System (ADS)

Fallah-Shorshani, Masoud; Shekarrizfard, Maryam; Hatzopoulou, Marianne

2017-10-01

Dispersion of road transport emissions in urban metropolitan areas is typically simulated using Gaussian models that ignore the turbulence and drag induced by buildings, which are especially relevant for areas with dense downtown cores. To consider the effect of buildings, street canyon models are used but often at the level of single urban corridors and small road networks. In this paper, we compare and validate two dispersion models with widely varying algorithms, across a modelling domain consisting of the City of Montreal, Canada accounting for emissions of more 40,000 roads. The first dispersion model is based on flow decomposition into the urban canopy sub-flow as well as overlying airflow. It takes into account the specific height and geometry of buildings along each road. The second model is a Gaussian puff dispersion model, which handles complex terrain and incorporates three-dimensional meteorology, but accounts for buildings only through variations in the initial vertical mixing coefficient. Validation against surface observations indicated that both models under-predicted measured concentrations. Average weekly exposure surfaces derived from both models were found to be reasonably correlated (r = 0.8) although the Gaussian dispersion model tended to underestimate concentrations around the roadways compared to the street canyon model. In addition, both models were used to estimate exposures of a representative sample of the Montreal population composed of 1319 individuals. Large differences were noted whereby exposures derived from the Gaussian puff model were significantly lower than exposures derived from the street canyon model, an expected result considering the concentration of population around roadways. These differences have large implications for the analyses of health effects associated with NO2 exposure.

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition

PubMed Central

Chang, Howard H.; Wang, Yujie; Hu, Xuefei; Lyapustin, Alexei

2017-01-01

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, ~70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations. PMID:29057838

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition

NASA Technical Reports Server (NTRS)

Belle, Jessica H.; Chang, Howard H.; Wang, Yujie; Hu, Xuefei; Lyapustin, Alexei; Liu, Yang

2017-01-01

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, approximately 70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations.

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition.

PubMed

Belle, Jessica H; Chang, Howard H; Wang, Yujie; Hu, Xuefei; Lyapustin, Alexei; Liu, Yang

2017-10-18

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM 2.5 ) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, ~70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM 2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM 2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM 2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM 2.5 concentrations.

Estimation of Anthropogenic Heat Emissions in Delhi, India and Their Role in Urban Heat Island Effect

NASA Astrophysics Data System (ADS)

Bhati, S.; Mohan, M.

2016-12-01

Energy consumption in the urban environment impacts the urban surface energy budget and leads to the emission of anthropogenic sensible heat into the atmosphere. Anthropogenic heat (AH) can vary both in time and space, and are not readily measured. In present study, anthropogenic heat emissions have been estimated using an inventory approach for Delhi. The main sources that have been considered are electricity consumption, vehicular emissions, fuel consumption in domestic sector and waste heat from power plants. Total estimated anthropogenic heat is apportioned gridwise (2 km2) and incorporated in the WRF (version 3.5) model coupled with single-layer Urban canopy model (UCM) to assess the impact of these emissions on urban heat island effect in Delhi. Vehicular emissions have been found to be highest contributor to anthropogenic heat emissions (47%) followed by electricity consumption (28%), domestic fuel consumption (16%) and waste heat from power plants (9%). Highest annual average anthropogenic heat flux was estimated to be 25.2 Wm-2. High flux zones are observed in east Delhi and densely occupied and commercial zones of Sitaram Bazar and Connaught Place. Inclusion of anthropogenic heat emissions in the model improves model performance for near surface temperature as well as urban heat island intensities. Maximum simulated night-time UHI improves from 5.95°C (without AH) to 6.24°C (with AH) against observed value of 6.68°C, thereby indicating positive contribution of anthropogenic heat emissions along with urban canopy towards UHI effect in Delhi. Similarly, spatial distribution and UHI hotspots are found to be comparatively closer to corresponding observed distribution and hotspots with anthropogenic heat emissions being added to the WRF model. Overall, relatively improved model performance is indicative of the impact of anthropogenic heat emissions in local urban meteorology and urban heat island effect in Delhi. Hence, rising population and change in land use-cover and associated anthropogenic activities call for strategic mitigation measures in the city to prevent further strengthening of heat island effect.

Impacts of future climate change on urban flood volumes in Hohhot in northern China: benefits of climate change mitigation and adaptations

NASA Astrophysics Data System (ADS)

Zhou, Qianqian; Leng, Guoyong; Huang, Maoyi

2018-01-01

As China becomes increasingly urbanised, flooding has become a regular occurrence in its major cities. Assessing the effects of future climate change on urban flood volumes is crucial to informing better management of such disasters given the severity of the devastating impacts of flooding (e.g. the 2016 flooding events across China). Although recent studies have investigated the impacts of future climate change on urban flooding, the effects of both climate change mitigation and adaptation have rarely been accounted for together in a consistent framework. In this study, we assess the benefits of mitigating climate change by reducing greenhouse gas (GHG) emissions and locally adapting to climate change by modifying drainage systems to reduce urban flooding under various climate change scenarios through a case study conducted in northern China. The urban drainage model - Storm Water Management Model - was used to simulate urban flood volumes using current and two adapted drainage systems (i.e. pipe enlargement and low-impact development, LID), driven by bias-corrected meteorological forcing from five general circulation models in the Coupled Model Intercomparison Project Phase 5 archive. Results indicate that urban flood volume is projected to increase by 52 % over 2020-2040 compared to the volume in 1971-2000 under the business-as-usual scenario (i.e. Representative Concentration Pathway (RCP) 8.5). The magnitudes of urban flood volumes are found to increase nonlinearly with changes in precipitation intensity. On average, the projected flood volume under RCP 2.6 is 13 % less than that under RCP 8.5, demonstrating the benefits of global-scale climate change mitigation efforts in reducing local urban flood volumes. Comparison of reduced flood volumes between climate change mitigation and local adaptation (by improving drainage systems) scenarios suggests that local adaptation is more effective than climate change mitigation in reducing future flood volumes. This has broad implications for the research community relative to drainage system design and modelling in a changing environment. This study highlights the importance of accounting for local adaptation when coping with future urban floods.

Impacts of future climate change on urban flood volumes in Hohhot in northern China: benefits of climate change mitigation and adaptations

DOE PAGES

Zhou, Qianqian; Leng, Guoyong; Huang, Maoyi

2018-01-15

As China becomes increasingly urbanised, flooding has become a regular occurrence in its major cities. Assessing the effects of future climate change on urban flood volumes is crucial to informing better management of such disasters given the severity of the devastating impacts of flooding (e.g. the 2016 flooding events across China). Although recent studies have investigated the impacts of future climate change on urban flooding, the effects of both climate change mitigation and adaptation have rarely been accounted for together in a consistent framework. In this study, we assess the benefits of mitigating climate change by reducing greenhouse gas (GHG)more » emissions and locally adapting to climate change by modifying drainage systems to reduce urban flooding under various climate change scenarios through a case study conducted in northern China. The urban drainage model – Storm Water Management Model – was used to simulate urban flood volumes using current and two adapted drainage systems (i.e. pipe enlargement and low-impact development, LID), driven by bias-corrected meteorological forcing from five general circulation models in the Coupled Model Intercomparison Project Phase 5 archive. Results indicate that urban flood volume is projected to increase by 52 % over 2020–2040 compared to the volume in 1971–2000 under the business-as-usual scenario (i.e. Representative Concentration Pathway (RCP) 8.5). The magnitudes of urban flood volumes are found to increase nonlinearly with changes in precipitation intensity. On average, the projected flood volume under RCP 2.6 is 13 % less than that under RCP 8.5, demonstrating the benefits of global-scale climate change mitigation efforts in reducing local urban flood volumes. Comparison of reduced flood volumes between climate change mitigation and local adaptation (by improving drainage systems) scenarios suggests that local adaptation is more effective than climate change mitigation in reducing future flood volumes. This has broad implications for the research community relative to drainage system design and modelling in a changing environment. Furthermore, this study highlights the importance of accounting for local adaptation when coping with future urban floods.« less

Impacts of future climate change on urban flood volumes in Hohhot in northern China: benefits of climate change mitigation and adaptations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Qianqian; Leng, Guoyong; Huang, Maoyi

As China becomes increasingly urbanised, flooding has become a regular occurrence in its major cities. Assessing the effects of future climate change on urban flood volumes is crucial to informing better management of such disasters given the severity of the devastating impacts of flooding (e.g. the 2016 flooding events across China). Although recent studies have investigated the impacts of future climate change on urban flooding, the effects of both climate change mitigation and adaptation have rarely been accounted for together in a consistent framework. In this study, we assess the benefits of mitigating climate change by reducing greenhouse gas (GHG)more » emissions and locally adapting to climate change by modifying drainage systems to reduce urban flooding under various climate change scenarios through a case study conducted in northern China. The urban drainage model – Storm Water Management Model – was used to simulate urban flood volumes using current and two adapted drainage systems (i.e. pipe enlargement and low-impact development, LID), driven by bias-corrected meteorological forcing from five general circulation models in the Coupled Model Intercomparison Project Phase 5 archive. Results indicate that urban flood volume is projected to increase by 52 % over 2020–2040 compared to the volume in 1971–2000 under the business-as-usual scenario (i.e. Representative Concentration Pathway (RCP) 8.5). The magnitudes of urban flood volumes are found to increase nonlinearly with changes in precipitation intensity. On average, the projected flood volume under RCP 2.6 is 13 % less than that under RCP 8.5, demonstrating the benefits of global-scale climate change mitigation efforts in reducing local urban flood volumes. Comparison of reduced flood volumes between climate change mitigation and local adaptation (by improving drainage systems) scenarios suggests that local adaptation is more effective than climate change mitigation in reducing future flood volumes. This has broad implications for the research community relative to drainage system design and modelling in a changing environment. Furthermore, this study highlights the importance of accounting for local adaptation when coping with future urban floods.« less

On the urban land-surface impact on climate over Central Europe

NASA Astrophysics Data System (ADS)

Huszar, Peter; Halenka, Tomas; Belda, Michal; Zemankova, Katerina; Zak, Michal

2014-05-01

For the purpose of qualifying and quantifying the impact of cities and in general the urban surfaces on climate over central Europe, the surface parameterization in regional climate model RegCM4 has been extended with the Single Layer Urban Canopy Model (SLUCM) for urban and suburban land surface. This can be used both in dynamic scale within BATS scheme and in a more detailed SUBBATS scale to treat the surface processes on a higher resolution subgrid. A set of experiments was performed over the period of 2005-2009 over central Europe, either without considering urban surfaces and with the SLUCM treatment. Results show a statistically significant impact of urbanized surfaces on temperature (up to 1.5 K increase in summer), on the boundary layer height (ZPBL, increases up to 50 m). Urbanization further influences surface wind with a winter decrease up to -0,6 m s-1 and both increases and decreases in summer depending the location with respect to cities and daytime (changes up to 0.3 ms-1). Urban surfaces significantly reduce evaporation and thus the humidity over the surface. This impacts in our simulations the summer precipitation rate showing decrease over cities up to - 2 mm day-1. We further showed, that significant temperature increases are not limited to the urban canopy layer but spawn the whole boundary layer. Above that, a small but statistically significant temperature decrease is modeled. The comparison with observational data showed significant improvement in modeling the monthly surface temperatures in summer and the models better describe the diurnal temperature variation reducing the afternoon and evening bias due to the UHI development, which was not captured by the model if one does not apply the urban parameterization. Sensitivity experiments were carried out as well to quantify the response of the meteorological conditions to changes in the parameters specific to the urban environment such as street width, building height, albedo of the roofs, anthropogenic heat release etc. and showed that the results are rather robust and the choice of the key SLUCM parameters impacts the results only slightly (mainly temperature, ZPBL and wind velocity). Further, the important conclusion is that statistically significant impacts are modeled not only over large urbanized areas (cities), but the influence of cities is evident over remote rural areas as well with minor or without any urban surfaces. We show that this is the result of the combined effect of the distant influence of surrounding cities and the influence of the minor local urban surface coverage.

Exploring a new method for the retrieval of urban thermophysical properties using thermal infrared remote sensing and deterministic modeling

NASA Astrophysics Data System (ADS)

De Ridder, K.; Bertrand, C.; Casanova, G.; Lefebvre, W.

2012-09-01

Increasingly, mesoscale meteorological and climate models are used to predict urban weather and climate. Yet, large uncertainties remain regarding values of some urban surface properties. In particular, information concerning urban values for thermal roughness length and thermal admittance is scarce. In this paper, we present a method to estimate values for thermal admittance in combination with an optimal scheme for thermal roughness length, based on METEOSAT-8/SEVIRI thermal infrared imagery in conjunction with a deterministic atmospheric model containing a simple urbanized land surface scheme. Given the spatial resolution of the SEVIRI sensor, the resulting parameter values are applicable at scales of the order of 5 km. As a study case we focused on the city of Paris, for the day of 29 June 2006. Land surface temperature was calculated from SEVIRI thermal radiances using a new split-window algorithm specifically designed to handle urban conditions, as described inAppendix A, including a correction for anisotropy effects. Land surface temperature was also calculated in an ensemble of simulations carried out with the ARPS mesoscale atmospheric model, combining different thermal roughness length parameterizations with a range of thermal admittance values. Particular care was taken to spatially match the simulated land surface temperature with the SEVIRI field of view, using the so-called point spread function of the latter. Using Bayesian inference, the best agreement between simulated and observed land surface temperature was obtained for the Zilitinkevich (1970) and Brutsaert (1975) thermal roughness length parameterizations, the latter with the coefficients obtained by Kanda et al. (2007). The retrieved thermal admittance values associated with either thermal roughness parameterization were, respectively, 1843 ± 108 J m-2 s-1/2 K-1 and 1926 ± 115 J m-2 s-1/2 K-1.

Using smartphone batteries as an urban thermometer

NASA Astrophysics Data System (ADS)

Droste, Arjan; Pape, Jan-Jaap; Overeem, Aart; Leijnse, Hidde; Steeneveld, Gert-Jan; Van Delden, Aarnout; Uijlenhoet, Remko

2017-04-01

Taking meteorological measurements in the urban environment is notoriously difficult due to the complex geometry at street and neighbourhood level. Traditional weather stations are absent in cities because of WMO regulations, so urban data has to come from typically expensive measurement-networks, or short intensive campaigns. While traditional measurements are scarce, there is an abundance of smart devices in cities: the well-known Internet of Things. It is for these reasons that crowdsourcing data has an enormous potential in cities, to deliver vast quantities of data without the maintenance costs of a measurement network. A promising source of potentially valuable data is the smartphone, because of its ubiquity and the many sensors most newer phone models now possess. Since most people nowadays have a smartphone, and carry it around wherever they go, data logged by the phone can be used to estimate the urban air temperature. A persistent log taken by nearly all smartphone models, even those without air temperature sensors, is the smartphone's battery temperature. The free OpenSignal smartphone application logs this battery temperature (among many other variables) and the position of the smartphone, which makes it possible to estimate the urban air temperature through a straightforward heat transfer model relating battery temperature to air and body temperature. The obtained urban temperatures are accurate within 1 to 2 degrees of certified measurement stations, proving the huge potential of this innovative method. This poster focuses on describing how thousands of daily smartphone battery temperature measurements can be translated to a relatively robust estimation of an urban air temperature, using 2 years of data from São Paulo in Brazil. Analysis of the results is presented in a separate session.

Analysis of the potential of near ground measurements of CO2 and CH4 in London, UK for the monitoring of city-scale emissions using an atmospheric transport model

NASA Astrophysics Data System (ADS)

Boon, A.; Broquet, G.; Clifford, D. J.; Chevallier, F.; Butterfield, D. M.; Pison, I.; Ramonet, M.; Paris, J. D.; Ciais, P.

2015-11-01

Carbon dioxide (CO2) and methane (CH4) mole fractions were measured at four near ground sites located in and around London during the summer of 2012 in view to investigate the potential of assimilating such measurements in an atmospheric inversion system for the monitoring of the CO2 and CH4 emissions in the London area. These data were analysed and compared with simulations using a modelling framework suited to building an inversion system: a 2 km horizontal resolution South of England configuration of the transport model CHIMERE driven by European Centre for Medium-Range Weather Forecasting (ECMWF) meteorological forcing, coupled to a 1 km horizontal resolution emission inventory (the UK National Atmospheric Emission Inventory). First comparisons reveal that local sources have a large impact on measurements and these local sources cannot be represented in the model at 2 km resolution. We evaluate methods to minimise some of the other critical sources of misfits between the observation data and the model simulation that overlap the signature of the errors in the emission inventory. These methods should make it easier to identify the corrections that should be applied to the inventory. Analysis is supported by observations from meteorological sites around the city and a three-week period of atmospheric mixing layer height estimations from lidar measurements. The difficulties of modelling the mixing layer depth and thus CO2 and CH4 concentrations during the night, morning and late afternoon led us to focus on the afternoon period for all further analyses. The misfits between observations and model simulations are high for both CO2 and CH4 (i.e., their root mean square (RMS) is between 8 and 12 parts per million (ppm) for CO2 and between 30 and 55 parts per billion (ppb) for CH4 at a given site). By analysing the gradients between the urban sites and a suburban or rural reference site, we are able to decrease the impact of uncertainties in the fluxes and transport outside the London area and in the model domain boundary conditions, and to better focus attention on the signature of London urban CO2 and CH4 emissions. This considerably improves the statistical agreement between the model and observations for CO2 (model-data RMS misfit of between 3 and 7 ppm) and to a lesser degree for CH4 (model-data RMS misfit of between 29 and 38 ppb). Between one of the urban sites and either reference site, selecting the gradients during periods wherein the reference site is upwind of the urban site further decreases the statistics of the misfits in general even though not systematically. In a final attempt to focus on the signature of the city anthropogenic emission in the mole fraction measurements, we use a theoretical ratio of gradients of CO to gradients of CO2 from fossil fuel emissions in the London area to diagnose observation based fossil fuel CO2 gradients, and compare them with the modelled ones. This estimate increases the consistency between the model and the measurements when considering one of the urban sites, but not when considering the other. While this study evaluates different approaches for increasing the consistency between the mesoscale model and the near ground data, and manages to decrease the random component of the analysed model data misfits to an extent that should not be prohibitive to extracting the signal from the London urban emissions, large biases remain in the final misfits. These biases are likely to be due to local emissions, to which the urban near ground sites are highly sensitive. This questions our current ability to exploit urban near ground data for the atmospheric inversion of city emissions based on models at spatial resolution coarser than 2 km.

Hybrid Air Quality Modeling Approach For Use in the Near ...

EPA Pesticide Factsheets

The Near-road EXposures to Urban air pollutant Study (NEXUS) investigated whether children with asthma living in close proximity to major roadways in Detroit, MI, (particularly near roadways with high diesel traffic) have greater health impacts associated with exposure to air pollutants than those living farther away. A major challenge in such health and exposure studies is the lack of information regarding pollutant exposure characterization. Air quality modeling can provide spatially and temporally varying exposure estimates for examining relationships between traffic-related air pollutants and adverse health outcomes. This paper presents a hybrid air quality modeling approach and its application in NEXUS in order to provide spatial and temporally varying exposure estimates and identification of the mobile source contribution to the total pollutant exposure. Model-based exposure metrics, associated with local variations of emissions and meteorology, were estimated using a combination of the AERMOD and R-LINE dispersion models, local emission source information from the National Emissions Inventory, detailed road network locations and traffic activity, and meteorological data from the Detroit City Airport. The regional background contribution was estimated using a combination of the Community Multiscale Air Quality (CMAQ) model and the Space/Time Ordinary Kriging (STOK) model. To capture the near-road pollutant gradients, refined “mini-grids” of model recep

Relationships between Changes in Urban Characteristics and Air Quality in East Asia from 2000 to 2010.

PubMed

Larkin, Andrew; van Donkelaar, Aaron; Geddes, Jeffrey A; Martin, Randall V; Hystad, Perry

2016-09-06

Characteristics of urban areas, such as density and compactness, are associated with local air pollution concentrations. The potential for altering air pollution through changing urban characteristics, however, is less certain, especially for expanding cities within the developing world. We examined changes in urban characteristics from 2000 to 2010 for 830 cities in East Asia to evaluate associations with changes in nitrogen dioxide (NO2) and fine particulate matter (PM2.5) air pollution. Urban areas were stratified by population size into small (100 000-250 000), medium, (250 000-1 000 000), and large (>1 000 000). Multivariate regression models including urban baseline characteristics, meteorological variables, and change in urban characteristics explained 37%, 49%, and 54% of the change in NO2 and 29%, 34%, and 37% of the change in PM2.5 for small, medium and large cities, respectively. Change in lights at night strongly predicted change in NO2 and PM2.5, while urban area expansion was strongly associated with NO2 but not PM2.5. Important differences between changes in urban characteristics and pollutant levels were observed by city size, especially NO2. Overall, changes in urban characteristics had a greater impact on NO2 and PM2.5 change than baseline characteristics, suggesting urban design and land use policies can have substantial impacts on local air pollution levels.

Meteorological overview and plume transport patterns during Cal-Mex 2010

NASA Astrophysics Data System (ADS)

Bei, Naifang; Li, Guohui; Zavala, Miguel; Barrera, Hugo; Torres, Ricardo; Grutter, Michel; Gutiérrez, Wilfredo; García, Manuel; Ruiz-Suarez, Luis Gerardo; Ortinez, Abraham; Guitierrez, Yaneth; Alvarado, Carlos; Flores, Israel; Molina, Luisa T.

2013-05-01

Cal-Mex 2010 Field Study is a US-Mexico collaborative project to investigate cross-border transport of emissions in the California-Mexico border region, which took place from May 15 to June 30, 2010. The current study presents an overview of the meteorological conditions and plume transport patterns during Cal-Mex 2010 based on the analysis of surface and vertical measurements (radiosonde, ceilometers and tethered balloon) conducted in Tijuana, Mexico and the modeling output using a trajectory model (FLEXPRT-WRF) and a regional model (WRF). The WRF model has been applied for providing the meteorological daily forecasts that are verified using the available observations. Both synoptic-scale and urban-scale forecasts (including wind, temperature, and humidity) agree reasonably well with the NCEP-FNL reanalysis data and the measurements; however, the WRF model frequently underestimates surface temperature and planetary boundary layer (PBL) height during nighttime compared to measurements. Based on the WRF-FLEXPART simulations with particles released in Tijuana in the morning, four representative plume transport patterns are identified as “plume-southeast”, “plume-southwest”, “plume-east” and “plume-north”, indicating the downwind direction of the plume; this will be useful for linking meteorological conditions with observed changes in trace gases and particular matter (PM). Most of the days during May and June are classified as plume-east and plume-southeast days, showing that the plumes in Tijuana are mostly carried to the southeast and east of Tijuana within the boundary layer during daytime. The plume transport directions are generally consistent with the prevailing wind directions on 850 hPa. The low level (below 800 m) wind, temperature, and moisture characteristics are different for each plume transport category according to the measurements from the tethered balloon. Future studies (such as using data assimilation and ensemble forecasts) will be performed to improve the temperature, wind and PBL simulations.

CO2 dispersion modelling over Paris region within the CO2-MEGAPARIS project

NASA Astrophysics Data System (ADS)

Lac, C.; Donnelly, R. P.; Masson, V.; Pal, S.; Donier, S.; Queguiner, S.; Tanguy, G.; Ammoura, L.; Xueref-Remy, I.

2012-10-01

Accurate simulation of the spatial and temporal variability of tracer mixing ratios over urban areas is challenging, but essential in order to utilize CO2 measurements in an atmospheric inverse framework to better estimate regional CO2 fluxes. This study investigates the ability of a high-resolution model to simulate meteorological and CO2 fields around Paris agglomeration, during the March field campaign of the CO2-MEGAPARIS project. The mesoscale atmospheric model Meso-NH, running at 2 km horizontal resolution, is coupled with the Town-Energy Balance (TEB) urban canopy scheme and with the Interactions between Soil, Biosphere and Atmosphere CO2-reactive (ISBA-A-gs) surface scheme, allowing a full interaction of CO2 between the surface and the atmosphere. Statistical scores show a good representation of the Urban Heat Island (UHI) and urban-rural contrasts. Boundary layer heights (BLH) at urban, sub-urban and rural sites are well captured, especially the onset time of the BLH increase and its growth rate in the morning, that are essential for tall tower CO2 observatories. Only nocturnal BLH at sub-urban sites are slightly underestimated a few nights, with a bias less than 50 m. At Eiffel tower, the observed spikes of CO2 maxima occur every morning exactly at the time at which the Atmospheric Boundary Layer (ABL) growth reaches the measurement height. The timing of the CO2 cycle is well captured by the model, with only small biases on CO2 concentrations, mainly linked to the misrepresentation of anthropogenic emissions, as the Eiffel site is at the heart of trafic emission sources. At sub-urban ground stations, CO2 measurements exhibit maxima at the beginning and at the end of each night, when the ABL is fully contracted, with a very strong spatio-temporal variability. The CO2 cycle at these sites is generally well reproduced by the model, even if some biases on the nocturnal maxima appear in the Paris plume parly due to small errors on the vertical transport, or in the vicinity of airports due to small errors on the horizontal transport (wind direction). A sensitivity test without urban parameterisation removes UHI and underpredicts nighttime BLH over urban and sub-urban sites, leading to large overestimation of nocturnal CO2 concentration at the sub-urban sites. The agreement of daytime and nighttime BLH and CO2 predictions of the reference simulation over Paris agglomeration demonstrates the potential of using the meso-scale system on urban and sub-urban area in the context of inverse modelling.

Detailed climate-change projections for urban land-use change and green-house gas increases for Belgium with COSMO-CLM coupled to TERRA_URB

NASA Astrophysics Data System (ADS)

Wouters, Hendrik; Vanden Broucke, Sam; van Lipzig, Nicole; Demuzere, Matthias

2016-04-01

Recent research clearly show that climate modelling at high resolution - which resolve the deep convection, the detailed orography and land-use including urbanization - leads to better modelling performance with respect to temperatures, the boundary-layer, clouds and precipitation. The increasing computational power enables the climate research community to address climate-change projections with higher accuracy and much more detail. In the framework of the CORDEX.be project aiming for coherent high-resolution micro-ensemble projections for Belgium employing different GCMs and RCMs, the KU Leuven contributes by means of the downscaling of EC-EARTH global climate model projections (provided by the Royal Meteorological Institute of the Netherlands) to the Belgian domain. The downscaling is obtained with regional climate simulations at 12.5km resolution over Europe (CORDEX-EU domain) and at 2.8km resolution over Belgium (CORDEX.be domain) using COSMO-CLM coupled to urban land-surface parametrization TERRA_URB. This is done for the present-day (1975-2005) and future (2040 → 2070 and 2070 → 2100). In these high-resolution runs, both GHG changes (in accordance to RCP8.5) and urban land-use changes (in accordance to a business-as-usual urban expansion scenario) are taken into account. Based on these simulations, it is shown how climate-change statistics are modified when going from coarse resolution modelling to high-resolution modelling. The climate-change statistics of particular interest are the changes in number of extreme precipitation events and extreme heat waves in cities. Hereby, it is futher investigated for the robustness of the signal change between the course and high-resolution and whether a (statistical) translation is possible. The different simulations also allow to address the relative impact and synergy between the urban expansion and increased GHG on the climate-change statistics. Hereby, it is investigated for which climate-change statistics the urban heat island and urban expansion is relevant, and to what extent the urban expansion can be included in the coarse-to-high resolution translation.

Air quality assessment in the periurban area of Mexico Megacity during dry hot season in 2011 and 2012

NASA Astrophysics Data System (ADS)

Garcia-Reynoso, Agustin; Santos Garcia-Yee, Jose; Barrera-Huertas, Hugo; Gerardo Ruiz-Suárez, Luis

2016-04-01

Air quality is a human health threat not only in urbanized areas, it also affects the surrounding zones. Interaction between urban and rural areas can be evaluated by measurements and using models for regional areas that includes in its domain the peri-urban regions. The use of monitoring sites in remote areas is useful however it is not possible to cover all the region the use of models can provide valuable information about the source and fate of the pollution and its transformation. In order to evaluate the influence of the Mexico Megacity in the air quality of the region, two field campaigns were performed during the dry hot season during 2011 and 2012. Meterological and pollutant measurements were made during February and march 2011, in three sites towards the south east of Mexico Megacity, and from march to April 2012 towards the west after the Popocatepetl-Iztaccihuatl mountain range. Air quality modeling were performed by using the National Emissions Inventory 2008 during the studied periods, a comparison between measurements and the air quality model was performed. This type of studies can offer information about the pollutant distribution, the meteorological conditions and the exactness of emissions inventories. The latest can be useful for emissions inventory developers and policy makers.

A numerical forecast model for road meteorology

NASA Astrophysics Data System (ADS)

Meng, Chunlei

2017-05-01

A fine-scale numerical model for road surface parameters prediction (BJ-ROME) is developed based on the Common Land Model. The model is validated using in situ observation data measured by the ROSA road weather stations of Vaisala Company, Finland. BJ-ROME not only takes into account road surface factors, such as imperviousness, relatively low albedo, high heat capacity, and high heat conductivity, but also considers the influence of urban anthropogenic heat, impervious surface evaporation, and urban land-use/land-cover changes. The forecast time span and the update interval of BJ-ROME in vocational operation are 24 and 3 h, respectively. The validation results indicate that BJ-ROME can successfully simulate the diurnal variation of road surface temperature both under clear-sky and rainfall conditions. BJ-ROME can simulate road water and snow depth well if the artificial removing was considered. Road surface energy balance in rainy days is quite different from that in clear-sky conditions. Road evaporation could not be neglected in road surface water cycle research. The results of sensitivity analysis show solar radiation correction coefficient, asphalt depth, and asphalt heat conductivity are important parameters in road interface temperatures simulation. The prediction results could be used as a reference of maintenance decision support system to mitigate the traffic jam and urban water logging especially in large cities.

Using Cool Roofs to Reduce Energy Use, Greenhouse Gas Emissions, and Urban Heat-island Effects: Findings from an India Experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akbari, Hashem; Xu, Tengfang; Taha, Haider

Cool roofs, cool pavements, and urban vegetation reduce energy use in buildings, lower local air pollutant concentrations, and decrease greenhouse gas emissions from urban areas. This report summarizes the results of a detailed monitoring project in India and related simulations of meteorology and air quality in three developing countries. The field results quantified direct energy savings from installation of cool roofs on individual commercial buildings. The measured annual energy savings potential from roof-whitening of previously black roofs ranged from 20-22 kWh/m2 of roof area, corresponding to an air-conditioning energy use reduction of 14-26% in commercial buildings. The study estimated thatmore » typical annual savings of 13-14 kWh/m2 of roof area could be achieved by applying white coating to uncoated concrete roofs on commercial buildings in the Metropolitan Hyderabad region, corresponding to cooling energy savings of 10-19%. With the assumption of an annual increase of 100,000 square meters of new roof construction for the next 10 years in the Metropolitan Hyderabad region, the annual cooling energy savings due to whitening concrete roof would be 13-14 GWh of electricity in year ten alone, with cumulative 10-year cooling energy savings of 73-79 GWh for the region. The estimated savings for the entire country would be at least 10 times the savings in Hyderabad, i.e., more than 730-790 GWh. We estimated that annual direct CO2 reduction associated with reduced energy use would be 11-12 kg CO2/m2 of flat concrete roof area whitened, and the cumulative 10-year CO2 reduction would be approximately 0.60-0.65 million tons in India. With the price of electricity estimated at seven Rupees per kWh, the annual electricity savings on air-conditioning would be approximately 93-101 Rupees per m2 of roof. This would translate into annual national savings of approximately one billion Rupees in year ten, and cumulative 10-year savings of over five billion Rupees for cooling energy in India. Meteorological simulations in this study indicated that a reduction of 2C in air temperature in the Hyderabad area would be likely if a combination of increased surface albedo and vegetative cover are used as urban heat-island control strategies. In addition, air-temperature reductions on the order of 2.5-3.5C could be achieved if moderate and aggressive heat-island mitigation measures are adopted, respectively. A large-scale deployment of mitigation measures can bring additional indirect benefit to the urban area. For example, cooling outside air can improve the efficiency of cooling systems, reduce smog and greenhouse gas (GHG) emissions, and indirectly reduce pollution from power plants - all improving environmental health quality. This study has demonstrated the effectiveness of cool-roof technology as one of the urban heat-island control strategies for the Indian industrial and scientific communities and has provided an estimate of the national energy savings potential of cool roofs in India. These outcomes can be used for developing cool-roof building standards and related policies in India. Additional field studies, built upon the successes and lessons learned from this project, may be helpful to further confirm the scale of potential energy savings from the application of cooler roofs in various regions of India. In the future, a more rigorous meteorological simulation using urbanized (meso-urban) meteorological models should be conducted, which may produce a more accurate estimate of the air-temperature reductions for the entire urban area.« less

Comparison of different methods for the assessment of the urban heat island in Stuttgart, Germany.

PubMed

Ketterer, Christine; Matzarakis, Andreas

2015-09-01

This study of the urban heat island (UHI) aims to support planning authorities by going beyond the traditional way of urban heat island studies. Therefore, air temperature as well as the physiologically equivalent temperature (PET) were applied to take into account the effect of the thermal atmosphere on city dwellers. The analysis of the urban heat island phenomenon of Stuttgart, Germany, includes a long-term frequency analysis using data of four urban and one rural meteorological stations. A (high resolution map) of the UHI intensity and PET was created using stepwise multiple linear regression based on data of car traverses as well as spatial data. The mapped conditions were classified according to the long-term frequency analysis. Regarding climate change, the need for adaptation measures as urban greening is obvious. Therefore, a spatial analysis of quantification of two scenarios of a chosen study area was done by the application of a micro-scale model. The nocturnal UHI of Stuttgart is during 15 % stronger than 4 K in the city center during summer when daytime heat stress occurs during 40 %. A typical summer condition is mapped using statistical approach to point out the most strained areas in Stuttgart center and west. According to the model results, the increase in number of trees in a chosen area (Olga hospital) can decrease PET by 0.5 K at 22:00 CET but by maximum 27 K at 14:00 CET.

Impacts of urbanisation on urban-rural water cycle: a China case study

NASA Astrophysics Data System (ADS)

Wang, Mingna; Singh, Shailesh Kumar; Zhang, Jun-e.; Khu, Soon Thiam

2016-04-01

Urbanization, which essentially create more impervious surface, is an inevitable part of modern societal development throughout the world. It produces several changes in the natural hydrological cycle by adding several processes. A better understanding of the impacts of urbanization, will allow policy makers to balance development and environment sustainability needs. It also helps underdeveloped countries make strategic decisions in their development process. The objective of this study is to understand and quantify the sensitivity of the urban-rural water cycle to urbanisation. A coupled hydrological model, MODCYCLE, was set up to simulate the effect of changes in landuse on daily streamflow and groundwater and applied to the Tianjin municipality, a rapidly urbanising mega-city on the east coast of China. The model uses landuse, land cover, soil, meteorological and climatic data to represent important parameters in the catchment. The fraction of impervious surface was used as a surrogate to quantify the degree of landuse change. In this work, we analysed the water cycle process under current urbanization situation in Tianjin. A number of different future development scenarios on based on increasing urbanisation intensity is explored. The results show that the expansion of urban areas had a great influence on generation of flow process and on ET, and the surface runoff was most sensitive to urbanisation. The results of these scenarios-based study about future urbanisation on hydrological system will help planners and managers in taking proper decisions regarding sustainable development.

Analyzing urban ecosystem variation in the City of Dongguan: A stepwise cluster modeling approach.

PubMed

Sun, J; Li, Y P; Gao, P P; Suo, C; Xia, B C

2018-06-13

In this study, a stepwise cluster modeling approach (SCMA) is developed for analyzing urban ecosystem variation via Normalized Difference Vegetation Index (NDVI). NDVI is an indicator of vegetation growth and coverage and useful in reflecting urban ecosystem. SCMA is established on a cluster tree that can characterize the complex relationship between independent and dependent variables. SCMA is applied to the City of Dongguan for simulating the urban NDVI and identifying associated drivers of human activity, topography and meteorology without specific functions. Results show that SCMA performances better than conventional statistical methods, illustrating the ability of SCMA in capturing the complex and nonlinear features of urban ecosystem. Results disclose that human activities play negative effects on NDVI due to the destruction of green space for pursuing more space for buildings. NDVI reduces gradually from the south part to the north part of Dongguan due to increased gross domestic product and population density, indicating that the ecosystem in Dongguan is better in the south part. NDVI in the northeast part (dominated by agriculture) is sensitive to the growth of economy and population. More attention should be paid to this part for sustainable development, such as increasing afforestation, planting grass and constructing parks. Precipitation has a positive effect on NDVI due to the promotion of soil moisture that is beneficial to plants' growth. Awareness of these complexities is helpful for sustainable development of urban ecosystem. Copyright © 2018 Elsevier Inc. All rights reserved.

Parameterizing Urban Canopy Layer transport in an Lagrangian Particle Dispersion Model

NASA Astrophysics Data System (ADS)

Stöckl, Stefan; Rotach, Mathias W.

2016-04-01

The percentage of people living in urban areas is rising worldwide, crossed 50% in 2007 and is even higher in developed countries. High population density and numerous sources of air pollution in close proximity can lead to health issues. Therefore it is important to understand the nature of urban pollutant dispersion. In the last decades this field has experienced considerable progress, however the influence of large roughness elements is complex and has as of yet not been completely described. Hence, this work studied urban particle dispersion close to source and ground. It used an existing, steady state, three-dimensional Lagrangian particle dispersion model, which includes Roughness Sublayer parameterizations of turbulence and flow. The model is valid for convective and neutral to stable conditions and uses the kernel method for concentration calculation. As most Lagrangian models, its lower boundary is the zero-plane displacement, which means that roughly the lower two-thirds of the mean building height are not included in the model. This missing layer roughly coincides with the Urban Canopy Layer. An earlier work "traps" particles hitting the lower model boundary for a recirculation period, which is calculated under the assumption of a vortex in skimming flow, before "releasing" them again. The authors hypothesize that improving the lower boundary condition by including Urban Canopy Layer transport could improve model predictions. This was tested herein by not only trapping the particles, but also advecting them with a mean, parameterized flow in the Urban Canopy Layer. Now the model calculates the trapping period based on either recirculation due to vortex motion in skimming flow regimes or vertical velocity if no vortex forms, depending on incidence angle of the wind on a randomly chosen street canyon. The influence of this modification, as well as the model's sensitivity to parameterization constants, was investigated. To reach this goal, the model was initialized and compared with meteorological and SF6 tracer measurements from the Basel UrBan Boundary Layer Experiment (BUBBLE). The proposed modification does not improve the model's agreement with concentration observations, even though the trapping time shows promising agreement with measurements. Additionally, the modification's influence is smaller than those of different turbulence profiles, zero-plane displacement height and Roughness Sublayer height.

Modeling and surface observations of arsenic dispersion from a large Cu-smelter in southwestern Europe

NASA Astrophysics Data System (ADS)

Chen, Bing; Stein, Ariel F.; Castell, Nuria; de la Rosa, Jesus D.; Sanchez de la Campa, Ana M.; Gonzalez-Castanedo, Yolanda; Draxler, Roland R.

2012-03-01

Arsenic is a toxic element for human health. Consequently, a mean annual target level for arsenic at 6 ng m-3 in PM10 was established by the European Directive 2004/107/CE to take effect January 2013. Cu-smelters can contribute to one-third of total emissions of arsenic in the atmosphere. Surface observations taken near a large Cu-smelter in the city of Huelva (Spain) show hourly arsenic concentrations in the range of 0-20 ng m-3. The arsenic peaks of 20 ng m-3 are higher than values normally observed in urban areas around Europe by a factor of 10. The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model has been employed to predict arsenic emissions, transport, and dispersion from the Cu-smelter. The model utilized outputs from different meteorological models and variations in the model physics options to simulate the uncertainty in the dispersion of the arsenic plume. Modeling outputs from the physics ensemble for each meteorological model driving HYSPLIT show the same number of arsenic peaks. HYSPLIT coupled with the Weather Research and Forecasting (WRF-ARW) meteorological output predicted the right number of peaks for arsenic concentration at the observation site. The best results were obtained when the WRF simulation used both four-dimensional data assimilation and surface analysis nudging. The prediction was good in local sea breeze circulations or when the flow was dominated by the synoptic scale prevailing winds. However, the predicted peak was delayed when the transport and dispersion was under the influence of an Atlantic cyclone. The calculated concentration map suggests that the plume from the Cu-smelter can cause arsenic pollution events in the city of Huelva as well as other cities and tourist areas in southwestern Spain.

New York Urban Hydro-Meteorological Testbed (NY-uHMT)

NASA Astrophysics Data System (ADS)

Norouzi, H.; Bah, A.

2017-12-01

It is well known that heat waves kill more persons, on average, than any other extreme weather event in the United States. New York City experiences much adversity due to inclement weather. Exploring climate variation in New Yorker City will help scientists and local government to detect and forecast extreme weather hazards and gather more localized temperature data within the five boroughs. Ground based weather stations are widely used to provide real time data to the public to prevent disasters. The New York urban Hydro-meteorological Testbed (NY-uHMT) is a hydro meteorological network that is used to investigate climate change in the New York City area. It is composed of twenty autonomous weather stations that will gather information on air temperature, relative humidity, rainfall and soil moisture properties around the densely populated NYC area. For each station, the data is stored on a Campbell Scientific CR200x data logger and can be accessed remotely using the LoggerNet software, or by direct connection using an RS-232 cable. Real-time weather data is acquired every fifteen minutes. The data is then periodically sampled and graphed through MATLAB code to be broadcasted on the uHMT website and is available at no charge to the public. We anticipate the results will show that the temperature, humidity, precipitation and soil moisture will vary from location to location depending on the magnitude of urbanization to the area.

A method to estimate spatiotemporal air quality in an urban traffic corridor.

PubMed

Singh, Nongthombam Premananda; Gokhale, Sharad

2015-12-15

Air quality exposure assessment using personal exposure sampling or direct measurement of spatiotemporal air pollutant concentrations has difficulty and limitations. Most statistical methods used for estimating spatiotemporal air quality do not account for the source characteristics (e.g. emissions). In this study, a prediction method, based on the lognormal probability distribution of hourly-average-spatial concentrations of carbon monoxide (CO) obtained by a CALINE4 model, has been developed and validated in an urban traffic corridor. The data on CO concentrations were collected at three locations and traffic and meteorology within the urban traffic corridor.(1) The method has been developed with the data of one location and validated at other two locations. The method estimated the CO concentrations reasonably well (correlation coefficient, r≥0.96). Later, the method has been applied to estimate the probability of occurrence [P(C≥Cstd] of the spatial CO concentrations in the corridor. The results have been promising and, therefore, may be useful to quantifying spatiotemporal air quality within an urban area. Copyright © 2015 Elsevier B.V. All rights reserved.

Influence of urban resilience measures in the magnitude and behaviour of energy fluxes in the city of Porto (Portugal) under a climate change scenario.

PubMed

Rafael, S; Martins, H; Sá, E; Carvalho, D; Borrego, C; Lopes, M

2016-10-01

Different urban resilience measures, such as the increase of urban green areas and the application of white roofs, were evaluated with the WRF-SUEWS modelling system. The case study consists of five heat waves occurring in Porto (Portugal) urban area in a future climate scenario. Meteorological forcing and boundary data were downscaled for Porto urban area from the CMIP5 earth system model MPI-ESM, for the Representative Concentration Pathway RCP8.5 scenario. The influence of different resilience measures on the energy balance components was quantified and compared between each other. Results show that the inclusion of green urban areas increases the evaporation and the availability of surface moisture, redirecting the energy to the form of latent heat flux (maximum increase of +200Wm(-2)) rather than to sensible heat. The application of white roofs increases the solar radiation reflection, due to the higher albedo of such surfaces, reducing both sensible and storage heat flux (maximum reductions of -62.8 and -35Wm(-2), respectively). The conjugations of the individual benefits related to each resilience measure shows that this measure is the most effective one in terms of improving the thermal comfort of the urban population, particularly due to the reduction of both sensible and storage heat flux. The obtained results contribute to the knowledge of the surface-atmosphere exchanges and can be of great importance for stakeholders and decision-makers. Copyright © 2016 Elsevier B.V. All rights reserved.

Numerical Simulation of Dispersion from Urban Greenhouse Gas Sources

NASA Astrophysics Data System (ADS)

Nottrott, Anders; Tan, Sze; He, Yonggang; Winkler, Renato

2017-04-01

Cities are characterized by complex topography, inhomogeneous turbulence, and variable pollutant source distributions. These features create a scale separation between local sources and urban scale emissions estimates known as the Grey-Zone. Modern computational fluid dynamics (CFD) techniques provide a quasi-deterministic, physically based toolset to bridge the scale separation gap between source level dynamics, local measurements, and urban scale emissions inventories. CFD has the capability to represent complex building topography and capture detailed 3D turbulence fields in the urban boundary layer. This presentation discusses the application of OpenFOAM to urban CFD simulations of natural gas leaks in cities. OpenFOAM is an open source software for advanced numerical simulation of engineering and environmental fluid flows. When combined with free or low cost computer aided drawing and GIS, OpenFOAM generates a detailed, 3D representation of urban wind fields. OpenFOAM was applied to model scalar emissions from various components of the natural gas distribution system, to study the impact of urban meteorology on mobile greenhouse gas measurements. The numerical experiments demonstrate that CH4 concentration profiles are highly sensitive to the relative location of emission sources and buildings. Sources separated by distances of 5-10 meters showed significant differences in vertical dispersion of plumes, due to building wake effects. The OpenFOAM flow fields were combined with an inverse, stochastic dispersion model to quantify and visualize the sensitivity of point sensors to upwind sources in various built environments. The Boussinesq approximation was applied to investigate the effects of canopy layer temperature gradients and convection on sensor footprints.

Development of a methodology examining the behaviours of VOCs source apportionment with micro-meteorology analysis in an urban and industrial area.

PubMed

Xiang, Yang; Delbarre, Hervé; Sauvage, Stéphane; Léonardis, Thierry; Fourmentin, Marc; Augustin, Patrick; Locoge, Nadine

2012-03-01

During summer 2009, online measurements of 25 Volatile Organic Compounds (VOCs) from C6 to C10 as well as micro-meteorological parameters were simultaneously performed in the industrial city of Dunkerque. With the obtained data set, we developed a methodology to examine how the contributions of different source categories depend on atmospheric turbulences, and the results provided identification of emission modes. Eight factors were resolved by using Positive Matrix Factorization model and three of them were associated with mixed sources. The observed behaviours of contributions with turbulences lead to attribute some factors with sources at ground level, and some other factors with sources in the upper part of surface layer. The impact of vertical turbulence on the pollutant dispersion is also affected by the distance between sources and receptor site. Copyright © 2011 Elsevier Ltd. All rights reserved.

Factors influencing mobile source particulate matter emissions-to-exposure relationships in the Boston urban area.

PubMed

Greco, Susan L; Wilson, Andrew M; Hanna, Steven R; Levy, Jonathan I

2007-11-15

Benefit-cost and regulatory impact analyses often use atmospheric dispersion models with coarse resolution to estimate the benefits of proposed mobile source emission control regulations. This approach may bias health estimates or miss important intra-urban variability for primary air pollutants. In this study, we estimate primary fine particulate matter (PM2.5) intake fractions (iF; the fraction of a pollutant emitted from a source that is inhaled by the population) for each of 23 398 road segments in the Boston Metro Core area to evaluate the potential for intra-urban variability in the emissions-to-exposure relationship. We estimate iFs using the CAL3QHCR line source model combined with residential populations within 5000 m of each road segment. The annual average values for the road segments range from 0.8 to 53 per million, with a mean of 12 per million. On average, 46% of the total exposure is realized within 200 m of the road segment, though this varies from 0 to 93% largely due to variable population patterns. Our findings indicate the likelihood of substantial intra-urban variability in mobile source primary PM2.5 iF that accounting for population movement with time, localized meteorological conditions, and street-canyon configurations would likely increase.

Air quality high resolution simulations of Italian urban areas with WRF-CHIMERE

NASA Astrophysics Data System (ADS)

Falasca, Serena; Curci, Gabriele

2017-04-01

The new European Directive on ambient air quality and cleaner air for Europe (2008/50/EC) encourages the use of modeling techniques to support the observations in the assessment and forecasting of air quality. The modelling system based on the combination of the WRF meteorological model and the CHIMERE chemistry-transport model is used to perform simulations at high resolution over the main Italian cities (e.g. Milan, Rome). Three domains covering Europe, Italy and the urban areas are nested with a decreasing grid size up to 1 km. Numerical results are produced for a winter month and a summer month of the year 2010 and are validated using ground-based observations (e.g. from the European air quality database AirBase). A sensitivity study is performed using different physics options, domain resolution and grid ratio; different urban parameterization schemes are tested using also characteristic morphology parameters for the cities considered. A spatial reallocation of anthropogenic emissions derived from international (e.g. EMEP, TNO, HTAP) and national (e.g. CTN-ACE) emissions inventories and based on the land cover datasets (Global Land Cover Facility and GlobCover) and the OpenStreetMap tool is also included. Preliminary results indicate that the introduction of the spatial redistribution at high-resolution allows a more realistic reproduction of the distribution of the emission flows and thus the concentrations of the pollutants, with significant advantages especially for the urban environments.

Model simulation of meteorology and air quality during the summer PUMA intensive measurement campaign in the UK West Midlands conurbation.

PubMed

Baggott, Sarah; Cai, Xiaoming; McGregor, Glenn; Harrison, Roy M

2006-05-01

The Regional Atmospheric Modeling System (RAMS) and Urban Airshed Model (UAM IV) have been implemented for prediction of air pollutant concentrations within the West Midlands conurbation of the United Kingdom. The modelling results for wind speed, direction and temperature are in reasonable agreement with observations for two stations, one in a rural area and the other in an urban area. Predictions of surface temperature are generally good for both stations, but the results suggest that the quality of temperature prediction is sensitive to whether cloud cover is reproduced reliably by the model. Wind direction is captured very well by the model, while wind speed is generally overestimated. The air pollution climate of the UK West Midlands is very different to those for which the UAM model was primarily developed, and the methods used to overcome these limitations are described. The model shows a tendency towards under-prediction of primary pollutant (NOx and CO) concentrations, but with suitable attention to boundary conditions and vertical profiles gives fairly good predictions of ozone concentrations. Hourly updating of chemical concentration boundary conditions yields the best results, with input of vertical profiles desirable. The model seriously underpredicts NO2/NO ratios within the urban area and this appears to relate to inadequate production of peroxy radicals. Overall, the chemical reactivity predicted by the model appears to fall well below that occurring in the atmosphere.

Surface Temperature Variation Prediction Model Using Real-Time Weather Forecasts

NASA Astrophysics Data System (ADS)

Karimi, M.; Vant-Hull, B.; Nazari, R.; Khanbilvardi, R.

2015-12-01

Combination of climate change and urbanization are heating up cities and putting the lives of millions of people in danger. More than half of the world's total population resides in cities and urban centers. Cities are experiencing urban Heat Island (UHI) effect. Hotter days are associated with serious health impacts, heart attaches and respiratory and cardiovascular diseases. Densely populated cities like Manhattan, New York can be affected by UHI impact much more than less populated cities. Even though many studies have been focused on the impact of UHI and temperature changes between urban and rural air temperature, not many look at the temperature variations within a city. These studies mostly use remote sensing data or typical measurements collected by local meteorological station networks. Local meteorological measurements only have local coverage and cannot be used to study the impact of UHI in a city and remote sensing data such as MODIS, LANDSAT and ASTER have with very low resolution which cannot be used for the purpose of this study. Therefore, predicting surface temperature in urban cities using weather data can be useful.Three months of Field campaign in Manhattan were used to measure spatial and temporal temperature variations within an urban setting by placing 10 fixed sensors deployed to measure temperature, relative humidity and sunlight. Fixed instrument shelters containing relative humidity, temperature and illumination sensors were mounted on lampposts in ten different locations in Manhattan (Vant-Hull et al, 2014). The shelters were fixed 3-4 meters above the ground for the period of three months from June 23 to September 20th of 2013 making measurements with the interval of 3 minutes. These high resolution temperature measurements and three months of weather data were used to predict temperature variability from weather forecasts. This study shows that the amplitude of spatial and temporal variation in temperature for each day can be predicted by regression of weather variables. In addition amplitude of spatial variations were most dependent on temperature, north winds, and high level lapse rate and the temporal variations were most dependent on temperature and lapse rates.

Human thermal comfort conditions and urban planning in hot-humid climates—The case of Cuba

NASA Astrophysics Data System (ADS)

Rodríguez Algeciras, José Abel; Coch, Helena; De la Paz Pérez, Guillermo; Chaos Yeras, Mabel; Matzarakis, Andreas

2016-08-01

Climate regional characteristics, urban environmental conditions, and outdoors thermal comfort requirements of residents are important for urban planning. Basic studies of urban microclimate can provide information and useful resources to predict and improve thermal conditions in hot-humid climatic regions. The paper analyzes the thermal bioclimate and its influence as urban design factor in Cuba, using Physiologically Equivalent Temperature (PET). Simulations of wind speed variations and shade conditions were performed to quantify changes in thermal bioclimate due to possible modifications in urban morphology. Climate data from Havana, Camagüey, and Santiago of Cuba for the period 2001 to 2012 were used to calculate PET with the RayMan model. The results show that changes in meteorological parameters influence the urban microclimate, and consequently modify the thermal conditions in outdoors spaces. Shade is the predominant strategy to improve urban microclimate with more significant benefits in terms of PET higher than 30 °C. For climatic regions such as the analyzed ones, human thermal comfort can be improved by a wind speed modification for thresholds of PET above 30 °C, and by a wind speed decreases in conditions below 26 °C. The improvement of human thermal conditions is crucial for urban sustainability. On this regards, our study is a contribution for urban designers, due to the possibility of taking advantage of results for improving microclimatic conditions based on urban forms. The results may enable urban planners to create spaces that people prefer to visit, and also are usable in the reconfiguration of cities.

Human thermal comfort conditions and urban planning in hot-humid climates-The case of Cuba.

PubMed

Rodríguez Algeciras, José Abel; Coch, Helena; De la Paz Pérez, Guillermo; Chaos Yeras, Mabel; Matzarakis, Andreas

2016-08-01

Climate regional characteristics, urban environmental conditions, and outdoors thermal comfort requirements of residents are important for urban planning. Basic studies of urban microclimate can provide information and useful resources to predict and improve thermal conditions in hot-humid climatic regions. The paper analyzes the thermal bioclimate and its influence as urban design factor in Cuba, using Physiologically Equivalent Temperature (PET). Simulations of wind speed variations and shade conditions were performed to quantify changes in thermal bioclimate due to possible modifications in urban morphology. Climate data from Havana, Camagüey, and Santiago of Cuba for the period 2001 to 2012 were used to calculate PET with the RayMan model. The results show that changes in meteorological parameters influence the urban microclimate, and consequently modify the thermal conditions in outdoors spaces. Shade is the predominant strategy to improve urban microclimate with more significant benefits in terms of PET higher than 30 °C. For climatic regions such as the analyzed ones, human thermal comfort can be improved by a wind speed modification for thresholds of PET above 30 °C, and by a wind speed decreases in conditions below 26 °C. The improvement of human thermal conditions is crucial for urban sustainability. On this regards, our study is a contribution for urban designers, due to the possibility of taking advantage of results for improving microclimatic conditions based on urban forms. The results may enable urban planners to create spaces that people prefer to visit, and also are usable in the reconfiguration of cities.

Sensitivity analysis of the near-road dispersion model RLINE - An evaluation at Detroit, Michigan

NASA Astrophysics Data System (ADS)

Milando, Chad W.; Batterman, Stuart A.

2018-05-01

The development of accurate and appropriate exposure metrics for health effect studies of traffic-related air pollutants (TRAPs) remains challenging and important given that traffic has become the dominant urban exposure source and that exposure estimates can affect estimates of associated health risk. Exposure estimates obtained using dispersion models can overcome many of the limitations of monitoring data, and such estimates have been used in several recent health studies. This study examines the sensitivity of exposure estimates produced by dispersion models to meteorological, emission and traffic allocation inputs, focusing on applications to health studies examining near-road exposures to TRAP. Daily average concentrations of CO and NOx predicted using the Research Line source model (RLINE) and a spatially and temporally resolved mobile source emissions inventory are compared to ambient measurements at near-road monitoring sites in Detroit, MI, and are used to assess the potential for exposure measurement error in cohort and population-based studies. Sensitivity of exposure estimates is assessed by comparing nominal and alternative model inputs using statistical performance evaluation metrics and three sets of receptors. The analysis shows considerable sensitivity to meteorological inputs; generally the best performance was obtained using data specific to each monitoring site. An updated emission factor database provided some improvement, particularly at near-road sites, while the use of site-specific diurnal traffic allocations did not improve performance compared to simpler default profiles. Overall, this study highlights the need for appropriate inputs, especially meteorological inputs, to dispersion models aimed at estimating near-road concentrations of TRAPs. It also highlights the potential for systematic biases that might affect analyses that use concentration predictions as exposure measures in health studies.

Size distribution and concentrations of heavy metals in atmospheric aerosols originating from industrial emissions as predicted by the HYSPLIT model

NASA Astrophysics Data System (ADS)

Chen, Bing; Stein, Ariel F.; Maldonado, Pabla Guerrero; Sanchez de la Campa, Ana M.; Gonzalez-Castanedo, Yolanda; Castell, Nuria; de la Rosa, Jesus D.

2013-06-01

This study presents a description of the emission, transport, dispersion, and deposition of heavy metals contained in atmospheric aerosols emitted from a large industrial complex in southern Spain using the HYSPLIT model coupled with high- (MM5) and low-resolution (GDAS) meteorological simulations. The dispersion model was configured to simulate eight size fractions (<0.33, 0.66, 1.3, 2.5, 5, 14, 17, and >17 μm) of metals based on direct measurements taken at the industrial emission stacks. Twelve stacks in four plants were studied and the stacks showed considerable differences for both emission fluxes and size ranges of metals. We model the dispersion of six major metals; Cr, Co, Ni, La, Zn, and Mo, which represent 77% of the total mass of the 43 measured elements. The prediction shows that the modeled industrial emissions produce an enrichment of heavy metals by a factor of 2-5 for local receptor sites when compared to urban and rural background areas in Spain. The HYSPLIT predictions based on the meteorological fields from MM5 show reasonable consistence with the temporal evolution of concentrations of Cr, Co, and Ni observed at three sites downwind of the industrial area. The magnitude of concentrations of metals at two receptors was underestimated for both MM5 (by a factor of 2-3) and GDAS (by a factor of 4-5) meteorological runs. The model prediction shows that heavy metal pollution from industrial emissions in this area is dominated by the ultra-fine (<0.66 μm) and fine (<2.5 μm) size fractions.

MOBIDIC-U: a watershed-scale model for stormwater attenuation through green infrastructures design

NASA Astrophysics Data System (ADS)

Ercolani, G.; Masseroni, D.; Chiaradia, E. A.; Bischetti, G. B.; Gandolfi, C.; Castelli, F.

2017-12-01

Surface water degradation resulting from the effects of urbanization on hydrology, water quality, habitat as well as ecological and environmental compartments represents an issue of primary focus for multiple agencies at the national, regional and local levels. Many management actions are needed throughout urban watersheds to achieve the desired effects on flow mitigation and pollutant reduction, but no single standardized solution can be effective in all locations. In this work, the distributed hydrological model MOBIDIC, already applied for hydrological balance simulations and flood prevention in different Italian regions, is adapted to the urban context (MOBIDIC-U) in order to evaluate alternative plans for stormwater quality management and flow abatement techniques through the adoption of green infrastructures (GIs). In particular the new modules included in MOBIDIC-U allow to (i) automatically define the upstream flow path as well as watershed boundary starting from a selected watershed closure point on the urban drainage network and (ii) obtain suitable graphical outputs for the visualization of flow peak and volume attenuation at the closure point. Moreover, MOBIDIC-U provides a public domain tool capable of evaluating the optimal location, type, and cost of the stormwater management practices needed to meet water quantity and quality goals. Despite the scalability of the model to different urban contexts, the current version of MOBIDIC-U has been developed for the area of the metropolitan city of Milan, Northern Italy. The model is implemented on a GIS platform, which already contains (i) the structure of the urban drainage network of the metropolitan city of Milan; (ii) the database of actual geomorphological and meteorological data for the previous domain (iii) the list of potential GIs, their standard size, installation and maintenance costs. Therefore, MOBIDIC-U provides an easy to use tool to local professionals to design and evaluate urban stormwater management measures based on GIs.

Assessing the Performance of a Network of Low Cost Particulate Matter Sensors Deployed in Sacramento, California

NASA Astrophysics Data System (ADS)

Mukherjee, A. D.; Brown, S. G.; McCarthy, M. C.

2017-12-01

A new generation of low cost air quality sensors have the potential to provide valuable information on the spatial-temporal variability of air pollution - if the measurements have sufficient quality. This study examined the performance of a particulate matter sensor model, the AirBeam (HabitatMap Inc., Brooklyn, NY), over a three month period in the urban environment of Sacramento, California. Nineteen AirBeam sensors were deployed at a regulatory air monitoring site collocated with meteorology measurements and as a local network over an 80 km2 domain in Sacramento, CA. This study presents the methodology to evaluate the precision, accuracy, and reliability of the sensors over a range of meteorological and aerosol conditions. The sensors demonstrated a robust degree of precision during collocated measurement periods (R2 = 0.98 - 0.99) and a moderate degree of correlation against a Beta Attenuation Monitor PM2.5 monitor (R2 0.6). A normalization correction is applied during the study period so that each AirBeam sensor in the network reports a comparable value. The role of the meteorological environment on the accuracy of the sensor measurements is investigated, along with the possibility of improving the measurements through a meteorology weighted correction. The data quality of the network of sensors is examined, and the spatial variability of particulate matter through the study domain derived from the sensor network is presented.

A computerized system to measure and predict air quality for emission control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crooks, G.; Ciccone, A.; Frattolillo, P.

1997-12-31

A Supplementary Emission Control (SEC) system has been developed on behalf of the Association Industrielle de l`Est de Montreal (AIEM). The objective of the SEC is to avoid exceedences of the Montreal Urban Community (MUC) 24 hour ambient Air Quality Standard (AQS) for sulphur dioxide in the industrial East Montreal area. The SEC system is comprised of: 3 continuous SO{sub 2} monitoring stations with data loggers and remote communications; a meteorological tower with data logger and modem for acquiring local meteorology; communications with Environment Canada to download meteorological forecast data; a polling PC for data retrieval; and Windows NT basedmore » software running on the AIEM computer server. The SEC software utilizes relational databases to store and maintain measured SO{sub 2} concentration data, emission data, as well as observed and forecast meteorological data. The SEC system automatically executes a numerical dispersion model to forecast SO{sub 2} concentrations up to six hours in the future. Based on measured SO{sub 2} concentrations at the monitoring stations and the six hour forecast concentrations, the system determines if local sources should reduce their emission levels to avoid potential exceedences of the AQS. The SEC system also includes a Graphical User Interface (GUI) for user access to the system. The SEC system and software are described, and the accuracy of the system at forecasting SO{sub 2} concentrations is examined.« less

Allocating emissions to 4 km and 1 km horizontal spatial resolutions and its impact on simulated NOx and O3 in Houston, TX

NASA Astrophysics Data System (ADS)

Pan, Shuai; Choi, Yunsoo; Roy, Anirban; Jeon, Wonbae

2017-09-01

A WRF-SMOKE-CMAQ air quality modeling system was used to investigate the impact of horizontal spatial resolution on simulated nitrogen oxides (NOx) and ozone (O3) in the Greater Houston area (a non-attainment area for O3). We employed an approach recommended by the United States Environmental Protection Agency to allocate county-based emissions to model grid cells in 1 km and 4 km horizontal grid resolutions. The CMAQ Integrated Process Rate analyses showed a substantial difference in emissions contributions between 1 and 4 km grids but similar NOx and O3 concentrations over urban and industrial locations. For example, the peak NOx emissions at an industrial and urban site differed by a factor of 20 for the 1 km and 8 for the 4 km grid, but simulated NOx concentrations changed only by a factor of 1.2 in both cases. Hence, due to the interplay of the atmospheric processes, we cannot expect a similar level of reduction of the gas-phase air pollutants as the reduction of emissions. Both simulations reproduced the variability of NASA P-3B aircraft measurements of NOy and O3 in the lower atmosphere (from 90 m to 4.5 km). Both simulations provided similar reasonable predictions at surface, while 1 km case depicted more detailed features of emissions and concentrations in heavily polluted areas, such as highways, airports, and industrial regions, which are useful in understanding the major causes of O3 pollution in such regions, and to quantify transport of O3 to populated communities in urban areas. The Integrated Reaction Rate analyses indicated a distinctive difference of chemistry processes between the model surface layer and upper layers, implying that correcting the meteorological conditions at the surface may not help to enhance the O3 predictions. The model-observation O3 bias in our studies (e.g., large over-prediction during the nighttime or along Gulf of Mexico coastline), were due to uncertainties in meteorology, chemistry or other processes. Horizontal grid resolution is unlikely the major contributor to these biases.

Airborne black carbon concentrations over an urban region in western India-temporal variability, effects of meteorology, and source regions.

PubMed

Bapna, Mukund; Sunder Raman, Ramya; Ramachandran, S; Rajesh, T A

2013-03-01

This study characterizes over 5 years of high time resolution (5 min), airborne black carbon (BC) concentrations (July 2003 to December 2008) measured over Ahmedabad, an urban region in western India. The data were used to obtain different time averages of BC concentrations, and these averages were then used to assess the diurnal, seasonal, and annual variability of BC over the study region. Assessment of diurnal variations revealed a strong association between BC concentrations and vehicular traffic. Peaks in BC concentration were co-incident with the morning (0730 to 0830, LST) and late evening (1930 to 2030, LST) rush hour traffic. Additionally, diurnal variability in BC concentrations during major festivals (Diwali and Dushera during the months of October/November) revealed an increase in BC concentrations due to fireworks displays. Maximum half hourly BC concentrations during the festival days were as high as 79.8 μg m(-3). However, the high concentrations rapidly decayed suggesting that local meteorology during the festive season was favorable for aerosol dispersion. A multiple linear regression (MLR) model with BC as the dependent variable and meteorological parameters as independent variables was fitted. The variability in temperature, humidity, wind speed, and wind direction accounted for about 49% of the variability in measured BC concentrations. Conditional probability function (CPF) analysis was used to identify the geographical location of local source regions contributing to the effective BC measured (at 880 nm) at the receptor site. The east north-east (ENE) direction to the receptor was identified as a major source region. National highway (NH8) and two coal-fired thermal power stations (at Gandhinagar and Sabarmati) were located in the identified direction, suggesting that local traffic and power plant emissions were likely contributors to the measured BC.

Gestational exposure to urban air pollution related to a decrease in cord blood vitamin d levels.

PubMed

Baïz, Nour; Dargent-Molina, Patricia; Wark, John D; Souberbielle, Jean-Claude; Slama, Rémy; Annesi-Maesano, Isabella

2012-11-01

Vitamin D deficiency has been implicated in the increased risk of several diseases. Exposure to air pollution has been suggested as a contributor to vitamin D deficiency. However, studies that have examined the effects of air pollution on vitamin D status are few and have never focused on prenatal life as an exposure window. Our aim was to investigate the associations between gestational exposure to urban air pollutants and 25-hydroxyvitamin D [25(OH)D] cord blood serum level in 375 mother-child pairs of the EDEN birth cohort. The Atmospheric Dispersion Modelling System (ADMS-Urban) pollution model, a validated dispersion model combining data on traffic conditions, topography, meteorology, and background pollution, was used to assess the concentrations of two major urban pollutants, particulate matter less than 10 μm in diameter (PM(10)) and nitrogen dioxide (NO(2)), at the mother's home address during pregnancy. Cord blood samples were collected at birth and were analyzed for levels of 25(OH)D. Maternal exposure to ambient urban levels of NO(2) and PM(10) during the whole pregnancy was a strong predictor of low vitamin D status in newborns. After adjustment, log-transformed 25(OH)D decreased by 0.15 U (P = 0.05) and 0.41 U (P = 0.04) for a 10-μg/m(3) increase in NO(2) and PM(10) pregnancy levels, respectively. The association was strongest for third-trimester exposures (P = 0.0003 and P = 0.004 for NO(2) and PM(10), respectively). Gestational exposure to ambient urban air pollution, especially during late pregnancy, may contribute to lower vitamin D levels in offspring. This could affect the child's risk of developing diseases later in life.

Development of a national anthropogenic heating database with an extrapolation for international cities

NASA Astrophysics Data System (ADS)

Sailor, David J.; Georgescu, Matei; Milne, Jeffrey M.; Hart, Melissa A.

2015-10-01

Given increasing utility of numerical models to examine urban impacts on meteorology and climate, there exists an urgent need for accurate representation of seasonally and diurnally varying anthropogenic heating data, an important component of the urban energy budget for cities across the world. Incorporation of anthropogenic heating data as inputs to existing climate modeling systems has direct societal implications ranging from improved prediction of energy demand to health assessment, but such data are lacking for most cities. To address this deficiency we have applied a standardized procedure to develop a national database of seasonally and diurnally varying anthropogenic heating profiles for 61 of the largest cities in the United Stated (U.S.). Recognizing the importance of spatial scale, the anthropogenic heating database developed includes the city scale and the accompanying greater metropolitan area. Our analysis reveals that a single profile function can adequately represent anthropogenic heating during summer but two profile functions are required in winter, one for warm climate cities and another for cold climate cities. On average, although anthropogenic heating is 40% larger in winter than summer, the electricity sector contribution peaks during summer and is smallest in winter. Because such data are similarly required for international cities where urban climate assessments are also ongoing, we have made a simple adjustment accounting for different international energy consumption rates relative to the U.S. to generate seasonally and diurnally varying anthropogenic heating profiles for a range of global cities. The methodological approach presented here is flexible and straightforwardly applicable to cities not modeled because of presently unavailable data. Because of the anticipated increase in global urban populations for many decades to come, characterizing this fundamental aspect of the urban environment - anthropogenic heating - is an essential element toward continued progress in urban climate assessment.

Spatial and seasonal patterns in urban influence on regional concentrations of speciated aerosols across the United States

NASA Astrophysics Data System (ADS)

Hand, J. L.; Schichtel, B. A.; Malm, W. C.; Pitchford, M.; Frank, N. H.

2014-11-01

Monthly, seasonal, and annual mean estimates of urban influence on regional concentrations of major aerosol species were computed using speciated aerosol data from the rural IMPROVE network (Interagency Monitoring of Protected Visual Environments) and the United States Environmental Protection Agency's urban Chemical Speciation Network for the 2008 through 2011 period. Aggregated for sites across the continental United States, the annual mean and one standard error in urban excess (defined as the ratio of urban to nearby rural concentrations) was highest for elemental carbon (3.3 ± 0.2), followed by ammonium nitrate (2.5 ± 0.2), particulate organic matter (1.78 ± 0.08), and ammonium sulfate (1.23 ± 0.03). The seasonal variability in urban excess was significant for carbonaceous aerosols and ammonium nitrate in the West, in contrast to the low seasonal variability in the urban influence of ammonium sulfate. Generally for all species, higher excess values in the West were associated with localized urban sources while in the East excess was more regional in extent. In addition, higher excess values in the western United States in winter were likely influenced not only by differences in sources but also by combined meteorological and topographic effects. This work has implications for understanding the spatial heterogeneity of major aerosol species near the interface of urban and rural regions and therefore for designing appropriate air quality management strategies. In addition, the spatial patterns in speciated mass concentrations provide constraints for regional and global models.

Energy flux parametrization as an opportunity to get Urban Heat Island insights: The case of Athens, Greece (Thermopolis 2009 Campaign).

PubMed

Loupa, G; Rapsomanikis, S; Trepekli, A; Kourtidis, K

2016-01-15

Energy flux parameterization was effected for the city of Athens, Greece, by utilizing two approaches, the Local-Scale Urban Meteorological Parameterization Scheme (LUMPS) and the Bulk Approach (BA). In situ acquired data are used to validate the algorithms of these schemes and derive coefficients applicable to the study area. Model results from these corrected algorithms are compared with literature results for coefficients applicable to other cities and their varying construction materials. Asphalt and concrete surfaces, canyons and anthropogenic heat releases were found to be the key characteristics of the city center that sustain the elevated surface and air temperatures, under hot, sunny and dry weather, during the Mediterranean summer. A relationship between storage heat flux plus anthropogenic energy flux and temperatures (surface and lower atmosphere) is presented, that results in understanding of the interplay between temperatures, anthropogenic energy releases and the city characteristics under the Urban Heat Island conditions.

Modeling nexus of urban heat island mitigation strategies with electricity/power usage and consumer costs: a case study for Phoenix, Arizona, USA

NASA Astrophysics Data System (ADS)

Silva, Humberto; Fillpot, Baron S.

2018-01-01

A reduction in both power and electricity usage was determined using a previously validated zero-dimensional energy balance model that implements mitigation strategies used to reduce the urban heat island (UHI) effect. The established model has been applied to show the change in urban characteristic temperature when executing four common mitigation strategies: increasing the overall (1) emissivity, (2) vegetated area, (3) thermal conductivity, and (4) albedo of the urban environment in a series of increases by 5, 10, 15, and 20% from baseline values. Separately, a correlation analysis was performed involving meteorological data and total daily energy (TDE) consumption where the 24-h average temperature was shown to have the greatest correlation to electricity service data in the Phoenix, Arizona, USA, metropolitan region. A methodology was then developed for using the model to predict TDE consumption reduction and corresponding cost-saving analysis when implementing the four mitigation strategies. The four modeled UHI mitigation strategies, taken in combination, would lead to the largest percent reduction in annual energy usage, where increasing the thermal conductivity is the single most effective mitigation strategy. The single least effective mitigation strategy, increasing the emissivity by 5% from the baseline value, resulted in an average calculated reduction of about 1570 GWh in yearly energy usage with a corresponding 157 million dollar cost savings. When the four parameters were increased in unison by 20% from baseline values, an average calculated reduction of about 2050 GWh in yearly energy usage was predicted with a corresponding 205 million dollar cost savings.

Modeling and identifying the sources of radiocesium contamination in separate sewerage systems.

PubMed

Pratama, Mochamad Adhiraga; Yoneda, Minoru; Yamashiki, Yosuke; Shimada, Yoko; Matsui, Yasuto

2018-05-01

The Fukushima Dai-ichi nuclear power plant accident released radiocesium in large amounts. The released radionuclides contaminated much of the surrounding environment, including sewers in urban areas of Fukushima prefecture. In this study we attempted to identify and quantify the sources of radiocesium contamination in separate sewerage systems and developed a compartment model based on the Radionuclide Migration in Urban Environments and Drainage Systems (MUD) model. Measurements of the time-dependent radiocesium concentration in sewer sludge combined with meteorological, demographic, and radiocesium dietary intake data indicated that rainfall-derived inflow and infiltration (RDII) and human excretion were the chief contributors of radiocesium contamination in a separate sewerage system. The quantities of contamination derived from RDII and human excretion were calculated and used in the modified MUD model to simulate radiocesium contamination in sewers in three urban areas in Fukushima prefecture: Fukushima, Koriyama, and Nihonmatsu Cities. The Nash efficiency coefficient (0.88-0.92) and determination coefficient (0.89-0.93) calculated in an evaluation of our compartment model indicated that the model produced satisfactory results. We also used the model to estimate the total volume of sludge with radiocesium concentrations in excess of the clearance level, based on the number of months elapsed after the accident. Estimations by our model suggested that wastewater treatment plants (WWTPs) in Fukushima, Koriyama, and Nihonmatsu generated about 1,750,000m 3 of radioactive sludge in total, a level in good agreement with the real data. Copyright © 2017 Elsevier B.V. All rights reserved.

Investigation of the Air Quality Change Effect on Gnss Signals

NASA Astrophysics Data System (ADS)

Gurbuz, G.; Gormus, K. S.; Altan, U.

2017-11-01

Air pollution is the most important environmental problem in Zonguldak city center. Since bituminous coal is used for domestic heating in houses and generating electricity in thermal power plants, particulate matter (PM10) is the leading air pollutant. Previous studies have shown that the water vapor in the troposphere is responsible for the tropospheric zenith delay in Global Navigation Satellite System (GNSS) measurements. In this study, data obtained from the ZONG GNSS station from Türkiye Ulusal Sabit GNSS Ağı (TUSAGA-Active network) in the central district of Zonguldak province, processed with GIPSY-OASIS II and GAMIT/GlobK software using the VMF1 mapping function, which is developed previously and considered to be the most accurate model. The resulting values were examined separately in terms of software. The meteorological parameters obtained from the Turkish State Meteorological Service and the air pollution values obtained from the Ministry of Environment and Urban Planning were analyzed and the zenith delay values were compared. When wet zenith delays of different days with different amounts of PM10 concentrations were examined in succession and under the same meteorological conditions, differences in the range of 20-40 mm on ZTD were observed.

DRIHM: Distributed Research Infrastructure for Hydro-Meteorology

NASA Astrophysics Data System (ADS)

Parodi, A.; Rebora, N.; Kranzlmueller, D.; Schiffers, M.; Clematis, A.; Tafferner, A.; Garrote, L. M.; Llasat Botija, M.; Caumont, O.; Richard, E.; Cros, P.; Dimitrijevic, V.; Jagers, B.; Harpham, Q.; Hooper, R. P.

2012-12-01

Hydro-Meteorology Research (HMR) is an area of critical scientific importance and of high societal relevance. It plays a key role in guiding predictions relevant to the safety and prosperity of humans and ecosystems from highly urbanized areas, to coastal zones, and to agricultural landscapes. Of special interest and urgency within HMR is the problem of understanding and predicting the impacts of severe hydro-meteorological events, such as flash-floods and landslides in complex orography areas, on humans and the environment, under the incoming climate change effects. At the heart of this challenge lies the ability to have easy access to hydrometeorological data and models, and facilitate the collaboration between meteorologists, hydrologists, and Earth science experts for accelerated scientific advances in this field. To face these problems the DRIHM (Distributed Research Infrastructure for Hydro-Meteorology) project is developing a prototype e-Science environment to facilitate this collaboration and provide end-to-end HMR services (models, datasets and post-processing tools) at the European level, with the ability to expand to global scale (e.g. cooperation with Earth Cube related initiatives). The objectives of DRIHM are to lead the definition of a common long-term strategy, to foster the development of new HMR models and observational archives for the study of severe hydrometeorological events, to promote the execution and analysis of high-end simulations, and to support the dissemination of predictive models as decision analysis tools. DRIHM combines the European expertise in HMR, in Grid and High Performance Computing (HPC). Joint research activities will improve the efficient use of the European e-Infrastructures, notably Grid and HPC, for HMR modelling and observational databases, model evaluation tool sets and access to HMR model results. Networking activities will disseminate DRIHM results at the European and global levels in order to increase the cohesion of European and possibly worldwide HMR communities and increase the awareness of ICT potential for HMR. Service activities will deploy the end-to-end DRIHM services and tools in support of HMR networks and virtual organizations on top of the existing European e-Infrastructures.

Simulation of the Transport and Dispersion of Perfluorocarbon Tracers Released in Texas Using multiple Assimilated Meteorological Wind Fields

NASA Astrophysics Data System (ADS)

Schichtel, B.; Barna, M.; Gebhart, K.; Green, M.

2002-12-01

The Big Bend Regional Aerosol and Visibility Observational Study (BRAVO) was designed to determine the causes of visibility impairment at Big Bend National Park, located in southwestern Texas. As part of BRAVO, an intensive field study was conducted during July-October 1999. Among the features of this study was the release of unique perfluorocarbon tracers from four sites within Texas, representative of industrial/urban locations. These tracers were monitored at 21 sites, throughout Texas. Other measurements collected during the field study included upper-level winds using radar profilers, and speciated fine-particulate mass concentrations. MM5 was used to simulate the regional meteorology during BRAVO, and was run in non-hydrostatic mode using a continental-scale 36km domain with nested 12km and 4km domains. MM5 employed observational nudging by incorporating the available measured wind data from the National Weather Service and data from the radar wind profilers. Meteorological data from the National Weather Service's Eta Data Assimilation System (EDAS), archived at 80km grid spacing, were also available. Several models are being used to evaluate airmass transport to Big Bend, including CMAQ, REMSAD, HYSPLIT and the CAPITA Monte Carlo Model. This combination of tracer data, meteorological data and deployment of four models provides a unique opportunity to assess the ability of the model/wind field combinations to properly simulate the regional scale atmospheric transport and dispersion of trace gases over distances of 100 to 800km. This paper will present the tracer simulations from REMSAD using the 36 and 12 km MM5 wind fields, and results from HYSPLIT and the Monte Carlo model driven by the 36km MM5 and 80km EDAS wind fields. Preliminary results from HYSPLIT and the Monte Carlo model driven by the EDAS wind fields shows that these models are able to account for the primary features of tracer concentrations patterns in the Big Bend area. However, at times the simulated concentration peaks proceeded or followed the actual measured concentrations by about at day and the duration of the simulated tracer impacts were shorter than those measured in the Big Bend area.

The University of Utah Urban Undertaking (U4)

NASA Astrophysics Data System (ADS)

Lin, J. C.; Mitchell, L.; Bares, R.; Mendoza, D. L.; Fasoli, B.; Bowling, D. R.; Garcia, M. A.; Buchert, M.; Pataki, D. E.; Crosman, E.; Horel, J.; Catharine, D.; Strong, C.; Ehleringer, J. R.

2015-12-01

The University of Utah is leading efforts to understand the spatiotemporal patterns in both emissions and concentrations of greenhouse gases (GHG) and criteria pollutants within urban systems. The urbanized corridor in northern Utah along the Wasatch Front, anchored by Salt Lake City, is undergoing rapid population growth that is projected to double in the next few decades. The Wasatch Front offers multiple advantages as an unique "urban laboratory": urban regions in multiple valleys spanning numerous orders of magnitude in population, each with unique airsheds, well-defined boundary conditions along deserts and tall mountains, strong signals during cold air pool events, seasonal contrasts in pollution, and a legacy of productive partnerships with local stakeholders and governments. We will show results from GHG measurements from the Wasatch Front, including one of the longest running continuous CO2 records in urban areas. Complementing this record are comprehensive meteorological observations and GHG/pollutant concentrations on mobile platforms: light rail, helicopter, and research vans. Variations in the GHG and pollutant observations illustrate human behavior and the resulting "urban metabolism" taking place on hourly, weekly, and seasonal cycles, resulting in a coupling between GHG and criteria pollutants. Moreover, these observations illustrate systematic spatial gradients in GHG and pollutant distributions between and within urban areas, traced to underlying gradients in population, energy use, terrain, and land use. Over decadal time scales the observations reveal growth of the "urban dome" due to expanding urban development. Using numerical models of the atmosphere, we further link concentrations of GHG and air quality-relevant pollutants to underlying emissions at the neighborhood scale as well as urban planning considerations.

Characterization of VOC sources in an urban area based on PTR-MS measurements and receptor modelling.

PubMed

Stojić, A; Stojić, S Stanišić; Šoštarić, A; Ilić, L; Mijić, Z; Rajšić, S

2015-09-01

In this study, the concentrations of volatile organic compounds were measured by the use of proton transfer reaction mass spectrometry, together with NO x , NO, NO2, SO2, CO and PM10 and meteorological parameters in an urban area of Belgrade during winter 2014. The multivariate receptor model US EPA Unmix was applied to the obtained dataset resolving six source profiles, which can be attributed to traffic-related emissions, gasoline evaporation/oil refineries, petrochemical industry/biogenic emissions, aged plumes, solid-fuel burning and local laboratories. Besides the vehicle exhaust, accounting for 27.6 % of the total mixing ratios, industrial emissions, which are present in three out of six resolved profiles, exert a significant impact on air quality in the urban area. The major contribution of regional and long-range transport was determined for source profiles associated with petrochemical industry/biogenic emissions (40 %) and gasoline evaporation/oil refineries (29 %) using trajectory sector analysis. The concentration-weighted trajectory model was applied with the aim of resolving the spatial distribution of potential distant sources, and the results indicated that emission sources from neighbouring countries, as well as from Slovakia, Greece, Poland and Scandinavian countries, significantly contribute to the observed concentrations.

Analysis of the effects of meteorology on aircraft exhaust dispersion and deposition using a Lagrangian particle model.

PubMed

Pecorari, Eliana; Mantovani, Alice; Franceschini, Chiara; Bassano, Davide; Palmeri, Luca; Rampazzo, Giancarlo

2016-01-15

The risk of air quality degradation is of considerable concern particularly for those airports that are located near urban areas. The ability to quantitatively predict the effects of air pollutants originated by airport operations is important for assessing air quality and the related impacts on human health. Current emission regulations have focused on local air quality in the proximity of airports. However, an integrated study should consider the effects of meteorological events, at both regional and local level, that can affect the dispersion and the deposition of exhausts. Rigorous scientific studies and extensive experimental data could contribute to the analysis of the impacts of airports expansion plans. This paper is focused on the analysis of the effects of meteorology on aircraft emission for the Marco Polo Airport in Venice. This is the most important international airport in the eastern part of the Po' Valley, one of the most polluted area in Europe. Air pollution is exacerbated by meteorology that is a combination of large and local scale effects that do not allow significant dispersion. Moreover, the airport is located near Venice, a city of noteworthy cultural and architectural relevance, and nearby the lagoon that hosts several areas of outstanding ecological importance at European level (Natura 2000 sites). Dispersion and deposit of the main aircraft exhausts (NOx, HC and CO) have been evaluated by using a Lagrangian particle model. Spatial and temporal aircraft exhaust dispersion has been analyzed for LTO cycle. Aircraft taxiing resulted to be the most impacting aircraft operation especially for the airport working area and its surroundings, however occasionally peaks may be observed even at high altitudes when cruise mode starts. Mixing height can affect concentrations more significantly than the concentrations in the exhausts themselves. An increase of HC and CO concentrations (15-50%) has been observed during specific meteorological events. Copyright © 2015 Elsevier B.V. All rights reserved.

Neural network model for the prediction of PM10 daily concentrations in two sites in the Western Mediterranean.

PubMed

de Gennaro, Gianluigi; Trizio, Livia; Di Gilio, Alessia; Pey, Jorge; Pérez, Noemi; Cusack, Michael; Alastuey, Andrés; Querol, Xavier

2013-10-01

An artificial neural network (ANN) was developed and tested to forecast PM10 daily concentration in two contrasted environments in NE Spain, a regional background site (Montseny), and an urban background site (Barcelona-CSIC), which was highly influenced by vehicular emissions. In order to predict 24-h average PM10 concentrations, the artificial neural network previously developed by Caselli et al. (2009) was improved by using hourly PM concentrations and deterministic factors such as a Saharan dust alert. In particular, the model input data for prediction were the hourly PM10 concentrations 1-day in advance, local meteorological data and information about air masses origin. The forecasted performance indexes for both sites were calculated and they showed better results for the regional background site in Montseny (R(2)=0.86, SI=0.75) than for urban site in Barcelona (R(2)=0.73, SI=0.58), influenced by local and sometimes unexpected sources. Moreover, a sensitivity analysis conducted to understand the importance of the different variables included among the input data, showed that local meteorology and air masses origin are key factors in the model forecasts. This result explains the reason for the improvement of ANN's forecasting performance at the Montseny site with respect to the Barcelona site. Moreover, the artificial neural network developed in this work could prove useful to predict PM10 concentrations, especially, at regional background sites such as those on the Mediterranean Basin which are primarily affected by long-range transports. Hence, the artificial neural network presented here could be a powerful tool for obtaining real time information on air quality status and could aid stakeholders in their development of cost-effective control strategies. © 2013 Elsevier B.V. All rights reserved.

South American mega cities: Knowledge gaps and collaboration opportunities

NASA Astrophysics Data System (ADS)

Gallardo, L.

2012-04-01

Urbanization and population concentration are outstanding phenomena in South America. About 83% of the 530 million South Americans live already in large coastal or near coastal cities (> 750 k inhabitants), many of which are heavily polluted. Curbing measures have been implemented on a relatively fast pace taking advantage of lessons learned elsewhere. However, as environmental objectives become more ambitious, considering for instance chronic health effects, impacts on ecosystems and agriculture, addressing secondary particles and climatic impacts, the need for cost-effective measures requires of more reliable and locally representative data. Such data include: emission fluxes (both natural and anthropogenic) and emission scenarios; characterization of vertical mixing; speciation and distribution of pollutants and precursors. In this presentation, we review the current situation in terms of atmospheric modeling, emission modeling, measuring and observations in a number of South American cities. Also, we describe low-cost actions oriented towards improving our understanding of: 1) vertical mixing by means of a modeling inter comparison exercise using data already collected in Santiago de Chile; 2) aerosol composition and speciation of volatile organic compounds by means of a coordinated sampling of filters and canisters at various locations highlighting the diversity of our cities. These actions were collectively convened by ca. 50 leading scientists and local policy makers during an international symposium held in Santiago in January 2012 (http://ossaf.cmm.uchile.cl/). This activity marked the closure of a five year project sponsored by the Inter American Institute on Global Change Research that tackled South American Emissions Megacities and Climate (SAEMC, CRN 2017). It was also a regional activity promoted and sponsored by the international Commission on Atmospheric Chemistry and Global Pollution (iCACGP), and by the World Meteorological Organization, Global Atmospheric Watch (GAW) Urban Research Meteorology and Environment (GURME).

Application and evaluation of the WRF-CMAQ modeling system to the 2011 DISCOVER-AQ Baltimore-Washington D.C. study

NASA Astrophysics Data System (ADS)

Appel, W.; Gilliam, R. C.; Pouliot, G. A.; Godowitch, J. M.; Pleim, J.; Hogrefe, C.; Kang, D.; Roselle, S. J.; Mathur, R.

2013-12-01

The DISCOVER-AQ project (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality), is a joint collaboration between NASA, U.S. EPA and a number of other local organizations with the goal of characterizing air quality in urban areas using satellite, aircraft, vertical profiler and ground based measurements (http://discover-aq.larc.nasa.gov). In July 2011, the DISCOVER-AQ project conducted intensive air quality measurements in the Baltimore, MD and Washington, D.C. area in the eastern U.S. To take advantage of these unique data, the Community Multiscale Air Quality (CMAQ) model, coupled with the Weather Research and Forecasting (WRF) model is used to simulate the meteorology and air quality in the same region using 12-km, 4-km and 1-km horizontal grid spacings. The goal of the modeling exercise is to demonstrate the capability of the coupled WRF-CMAQ modeling system to simulate air quality at fine grid spacings in an urban area. Development of new data assimilation techniques and the use of higher resolution input data for the WRF model have been implemented to improve the meteorological results, particularly at the 4-km and 1-km grid resolutions. In addition, a number of updates to the CMAQ model were made to enhance the capability of the modeling system to accurately represent the magnitude and spatial distribution of pollutants at fine model resolutions. Data collected during the 2011 DISCOVER-AQ campaign, which include aircraft transects and spirals, ship measurements in the Chesapeake Bay, ozonesondes, tethered balloon measurements, DRAGON aerosol optical depth measurements, LIDAR measurements, and intensive ground-based site measurements, are used to evaluate results from the WRF-CMAQ modeling system for July 2011 at the three model grid resolutions. The results of the comparisons of the model results to these measurements will be presented, along with results from the various sensitivity simulations examining the impact the various updates to the modeling system have on the model estimates.

Relative roles of emissions and meteorology in the diurnal pattern of urban PM10: analysis of the daylight saving time effect.

PubMed

Muñoz, Ricardo C

2012-06-01

Daylight saving time (DST) is a common practice in many countries, in which Official Time (OT) is abruptly shifted 1 hour with respect to solar time on two occasions every year (in fall and spring). All anthropogenic emitting processes tied to OT like job and school commuting traffic, abruptly change in this moment their timing with respect to solar time, inducing a sudden shift between emissions and the meteorological factors that control the dispersion and transport of air pollutants. Analyzing 13 years of hourly particulate matter (PM10) concentrations measured in Santiago, Chile, we demonstrate that the DST practice has observable non-trivial effects in the PM10 diurnal cycle. The clearest impact is in the morning peak of PM10 during the fall DST change, which occurs later and has on average a significant smaller magnitude in the days after the DST change as compared to the days before it. This decrease in magnitude is most remarkable because it occurs in a period of the year when overall PM10 concentrations increase due to generally worsening of the dispersion conditions. Results are shown for seven monitoring stations around the city, and for the fall and spring DST changes. They show clearly the interplay of emissions and meteorology in conditioning urban air pollution problems, highlighting the role of the morning and evening transitions of the atmospheric boundary layer in shaping the diurnal pattern of urban air pollutant concentrations.

Distribution and urban-suburban differences in ground-level ozone and its precursors over Shenyang, China

NASA Astrophysics Data System (ADS)

Liu, Ningwei; Ren, Wanhui; Li, Xiaolan; Ma, Xiaogang; Zhang, Yunhai; Li, Bingkun

2018-03-01

Hourly mixing ratio data of ground-level ozone and its main precursors at ambient air quality monitoring sites in Shenyang during 2013-2015 were used to survey spatiotemporal variations in ozone. Then, the transport of ozone and its precursors among urban, suburban, and rural sites was examined. The correlations between ozone and some key meteorological factors were also investigated. Ozone and O x mixing ratios in Shenyang were higher during warm seasons and lower during cold ones, while ozone precursors followed the opposite cycle. Ozone mixing ratios reached maximum and minimum values in the afternoon and morning, respectively, reflecting the significant influence of photochemical production during daytime and depletion via titration during nighttime. Compared to those in downtown Shenyang, ozone mixing ratios were higher and the occurrence of peak values were later in suburban and rural areas downwind of the prevailing wind. The differences were most significant in summer, when the ozone mixing ratios at one suburban downwind site reached a maximum value of 35.6 ppb higher than those at the downtown site. This suggests that photochemical production processes were significant during the transport of ozone precursors, particularly in warm seasons with sufficient sunlight. Temperature, total radiation, and wind speed all displayed positive correlations with ozone concentration, reflecting their important role in accelerating ozone formation. Generally, the correlations between ozone and meteorological factors were slightly stronger at suburban sites than in urban areas, indicating that ozone levels in suburban areas were more sensitive to these meteorological factors.

Fine particulate (PM2.5) dynamics during rapid urbanization in Beijing, 1973–2013

PubMed Central

Han, Lijian; Zhou, Weiqi; Li, Weifeng

2016-01-01

PM2.5 has been given special concern in recent years when the air quality monitoring station started recording. However, long-term PM2.5 concentration dynamic analysis cannot be taken with the limited observations. We therefore estimated the PM2.5 concentration using meteorological visibility data in Beijing. We found that 71 ± 17% of PM10 were PM2.5, which contributed to visibility impairment (y = 332.26e−0.232x; R2 = 0.75, P < 0.05). We then reconstructed a time series of annual PM2.5 from 1973 to 2013, and examined its relationship with urbanization by indicators of population, gross domestic production (GDP), energy consumption, and number of vehicles. Concluded that 1) Meteorological conditions were not the major cause of PM2.5 increase from 1973 to 2013; 2) With population and GDP growth, PM2.5 increased significantly (R2 = 0.5917, P < 0.05; R2 = 0.5426, P < 0.05); 3) Intensive human activity could change air quality in a short period, as observed changes in the correlations of PM2.5 concentration with energy consumption and number of vehicles before and after 2004, respectively. The success of this research provides an easy way in reconstructing long-term PM2.5 concentration with limited PM2.5 observation and meteorological visibility, and insight the impact of urbanization on air quality. PMID:27031598

Quantification and mapping of urban fluxes under climate change: Application of WRF-SUEWS model to Greater Porto area (Portugal).

PubMed

Rafael, S; Martins, H; Marta-Almeida, M; Sá, E; Coelho, S; Rocha, A; Borrego, C; Lopes, M

2017-05-01

Climate change and the growth of urban populations are two of the main challenges facing Europe today. These issues are linked as climate change results in serious challenges for cities. Recent attention has focused on how urban surface-atmosphere exchanges of heat and water will be affected by climate change and the implications for urban planning and sustainability. In this study energy fluxes for Greater Porto area, Portugal, were estimated and the influence of the projected climate change evaluated. To accomplish this, the Weather Research and Forecasting Model (WRF) and the Surface Urban Energy and Water Balance Scheme (SUEWS) were applied for two climatological scenarios: a present (or reference, 1986-2005) scenario and a future scenario (2046-2065), in this case the Representative Concentration Pathway RCP8.5, which reflects the worst set of expectations (with the most onerous impacts). The results show that for the future climate conditions, the incoming shortwave radiation will increase by around 10%, the sensible heat flux around 40% and the net storage heat flux around 35%. In contrast, the latent heat flux will decrease about 20%. The changes in the magnitude of the different fluxes result in an increase of the net all-wave radiation by 15%. The implications of the changes of the energy balance on the meteorological variables are discussed, particularly in terms of temperature and precipitation. Copyright © 2017 Elsevier Inc. All rights reserved.

Development of a distributed air pollutant dry deposition modeling framework.

PubMed

Hirabayashi, Satoshi; Kroll, Charles N; Nowak, David J

2012-12-01

A distributed air pollutant dry deposition modeling system was developed with a geographic information system (GIS) to enhance the functionality of i-Tree Eco (i-Tree, 2011). With the developed system, temperature, leaf area index (LAI) and air pollutant concentration in a spatially distributed form can be estimated, and based on these and other input variables, dry deposition of carbon monoxide (CO), nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), and particulate matter less than 10 microns (PM10) to trees can be spatially quantified. Employing nationally available road network, traffic volume, air pollutant emission/measurement and meteorological data, the developed system provides a framework for the U.S. city managers to identify spatial patterns of urban forest and locate potential areas for future urban forest planting and protection to improve air quality. To exhibit the usability of the framework, a case study was performed for July and August of 2005 in Baltimore, MD. Copyright © 2012 Elsevier Ltd. All rights reserved.

Trip-oriented travel time prediction (TOTTP) with historical vehicle trajectories

NASA Astrophysics Data System (ADS)

Xu, Tao; Li, Xiang; Claramunt, Christophe

2018-06-01

Accurate travel time prediction is undoubtedly of importance to both traffic managers and travelers. In highly-urbanized areas, trip-oriented travel time prediction (TOTTP) is valuable to travelers rather than traffic managers as the former usually expect to know the travel time of a trip which may cross over multiple road sections. There are two obstacles to the development of TOTTP, including traffic complexity and traffic data coverage.With large scale historical vehicle trajectory data and meteorology data, this research develops a BPNN-based approach through integrating multiple factors affecting trip travel time into a BPNN model to predict trip-oriented travel time for OD pairs in urban network. Results of experiments demonstrate that it helps discover the dominate trends of travel time changes daily and weekly, and the impact of weather conditions is non-trivial.

Persistent Drought Social-Ecological Regime Shift and Migration among Agricultural Communities in Bundelkhand Region India

NASA Astrophysics Data System (ADS)

Alam, Parvej

2017-04-01

Drought is a hydro-meteorological syndrome of 'prolonged period of water scarcity affecting natural resources, environment and, thereby, the people'. Different parts of India suffer from drought incidences of varying periodicity, with all 13 districts of Bundelkhand region repeatedly declared as drought-prone. Spread over the states of Uttar Pradesh and Madhya Pradesh, Bundelkhand falls in the rain shadow, semi-arid zone of the northern extreme of Peninsular India. In recent years, because of changing pattern of monsoons across India, rainfall in Bundelkhand in addition to being deficient has also become unpredictable. Such unpredictability has made agriculture in Bundelkhand region a risky and less attractive proposition and farmers are increasingly forgoing agriculture in villages in favour of livelihood opportunities in urban areas. Thus, there has been a constant flow of rural to urban migration in towns and cities in Bundelkhand. The present study analyses the changing land use pattern of Bundelkhand with the help of land use classification and explores the trend of rural-urban migration in Bundelkhand in the light of Galor's Model of Migration. In the current work, Climate Change is taken as a major driver behind migration decision and with the help of primary survey, a two-generational, inter regional model based on Galor's model has been developed. Keywords: Bundelkhand, Drought, Migration, Galor's Model

Estimating Regional Spatial and Temporal Variability of PM2.5 Concentrations Using Satellite Data, Meteorology, and Land Use Information

PubMed Central

Liu, Yang; Paciorek, Christopher J.; Koutrakis, Petros

2009-01-01

Background Studies of chronic health effects due to exposures to particulate matter with aerodynamic diameters ≤ 2.5 μm (PM2.5) are often limited by sparse measurements. Satellite aerosol remote sensing data may be used to extend PM2.5 ground networks to cover a much larger area. Objectives In this study we examined the benefits of using aerosol optical depth (AOD) retrieved by the Geostationary Operational Environmental Satellite (GOES) in conjunction with land use and meteorologic information to estimate ground-level PM2.5 concentrations. Methods We developed a two-stage generalized additive model (GAM) for U.S. Environmental Protection Agency PM2.5 concentrations in a domain centered in Massachusetts. The AOD model represents conditions when AOD retrieval is successful; the non-AOD model represents conditions when AOD is missing in the domain. Results The AOD model has a higher predicting power judged by adjusted R2 (0.79) than does the non-AOD model (0.48). The predicted PM2.5 concentrations by the AOD model are, on average, 0.8–0.9 μg/m3 higher than the non-AOD model predictions, with a more smooth spatial distribution, higher concentrations in rural areas, and the highest concentrations in areas other than major urban centers. Although AOD is a highly significant predictor of PM2.5, meteorologic parameters are major contributors to the better performance of the AOD model. Conclusions GOES aerosol/smoke product (GASP) AOD is able to summarize a set of weather and land use conditions that stratify PM2.5 concentrations into two different spatial patterns. Even if land use regression models do not include AOD as a predictor variable, two separate models should be fitted to account for different PM2.5 spatial patterns related to AOD availability. PMID:19590678

Development of a modular streamflow model to quantify runoff contributions from different land uses in tropical urban environments using Genetic Programming

NASA Astrophysics Data System (ADS)

Meshgi, Ali; Schmitter, Petra; Chui, Ting Fong May; Babovic, Vladan

2015-06-01

The decrease of pervious areas during urbanization has severely altered the hydrological cycle, diminishing infiltration and therefore sub-surface flows during rainfall events, and further increasing peak discharges in urban drainage infrastructure. Designing appropriate waster sensitive infrastructure that reduces peak discharges requires a better understanding of land use specific contributions towards surface and sub-surface processes. However, to date, such understanding in tropical urban environments is still limited. On the other hand, the rainfall-runoff process in tropical urban systems experiences a high degree of non-linearity and heterogeneity. Therefore, this study used Genetic Programming to establish a physically interpretable modular model consisting of two sub-models: (i) a baseflow module and (ii) a quick flow module to simulate the two hydrograph flow components. The relationship between the input variables in the model (i.e. meteorological data and catchment initial conditions) and its overall structure can be explained in terms of catchment hydrological processes. Therefore, the model is a partial greying of what is often a black-box approach in catchment modelling. The model was further generalized to the sub-catchments of the main catchment, extending the potential for more widespread applications. Subsequently, this study used the modular model to predict both flow components of events as well as time series, and applied optimization techniques to estimate the contributions of various land uses (i.e. impervious, steep grassland, grassland on mild slope, mixed grasses and trees and relatively natural vegetation) towards baseflow and quickflow in tropical urban systems. The sub-catchment containing the highest portion of impervious surfaces (40% of the area) contributed the least towards the baseflow (6.3%) while the sub-catchment covered with 87% of relatively natural vegetation contributed the most (34.9%). The results from the quickflow module revealed average runoff coefficients between 0.12 and 0.80 for the various land uses and decreased from impervious (0.80), grass on steep slopes (0.56), grass on mild slopes (0.48), mixed grasses and trees (0.42) to relatively natural vegetation (0.12). The established modular model, reflecting the driving hydrological processes, enables the quantification of land use specific contributions towards the baseflow and quickflow components. This quantification facilitates the integration of water sensitive urban infrastructure for the sustainable development of water in tropical megacities.

Network design for quantifying urban CO2 emissions: assessing trade-offs between precision and network density

NASA Astrophysics Data System (ADS)

Turner, Alexander J.; Shusterman, Alexis A.; McDonald, Brian C.; Teige, Virginia; Harley, Robert A.; Cohen, Ronald C.

2016-11-01

The majority of anthropogenic CO2 emissions are attributable to urban areas. While the emissions from urban electricity generation often occur in locations remote from consumption, many of the other emissions occur within the city limits. Evaluating the effectiveness of strategies for controlling these emissions depends on our ability to observe urban CO2 emissions and attribute them to specific activities. Cost-effective strategies for doing so have yet to be described. Here we characterize the ability of a prototype measurement network, modeled after the Berkeley Atmospheric CO2 Observation Network (BEACO2N) in California's Bay Area, in combination with an inverse model based on the coupled Weather Research and Forecasting/Stochastic Time-Inverted Lagrangian Transport (WRF-STILT) to improve our understanding of urban emissions. The pseudo-measurement network includes 34 sites at roughly 2 km spacing covering an area of roughly 400 km2. The model uses an hourly 1 × 1 km2 emission inventory and 1 × 1 km2 meteorological calculations. We perform an ensemble of Bayesian atmospheric inversions to sample the combined effects of uncertainties of the pseudo-measurements and the model. We vary the estimates of the combined uncertainty of the pseudo-observations and model over a range of 20 to 0.005 ppm and vary the number of sites from 1 to 34. We use these inversions to develop statistical models that estimate the efficacy of the combined model-observing system in reducing uncertainty in CO2 emissions. We examine uncertainty in estimated CO2 fluxes on the urban scale, as well as for sources embedded within the city such as a line source (e.g., a highway) or a point source (e.g., emissions from the stacks of small industrial facilities). Using our inversion framework, we find that a dense network with moderate precision is the preferred setup for estimating area, line, and point sources from a combined uncertainty and cost perspective. The dense network considered here (modeled after the BEACO2N network with an assumed mismatch error of 1 ppm at an hourly temporal resolution) could estimate weekly CO2 emissions from an urban region with less than 5 % error, given our characterization of the combined observation and model uncertainty.

The Urban Heat Island Phenomenon and Potential Mitigation Strategies

NASA Technical Reports Server (NTRS)

Estes, Maurice G., Jr.; Gorsevski, Virginia; Russell, Camille; Quattrochi, Dale; Luvall, Jeffrey

1999-01-01

A survey of urban heat island research is provided to describe how heat islands develop, urban landscape and meteorological characteristics that facilitate development, use of aircraft remote sensing data, and why heat islands are of interest to planners, elected officials, and the public. The roles of the National Aeronautics and Space Administration (NASA), the Environmental Protection Agency (EPA), other federal agencies, national laboratories and universities, state and local governments, and non-governmental organizations (NGOS) in studying the urban heat island effect and developing mitigation strategies are explored. Barriers that hamper mitigation efforts and case studies in Atlanta and Salt Lake City are discussed.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Yuyu; Smith, Steven J.; Elvidge, Christopher

Accurate information of urban areas at regional and global scales is important for both the science and policy-making communities. The Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime stable light data (NTL) provide a potential way to map urban area and its dynamics economically and timely. In this study, we developed a cluster-based method to estimate the optimal thresholds and map urban extents from the DMSP/OLS NTL data in five major steps, including data preprocessing, urban cluster segmentation, logistic model development, threshold estimation, and urban extent delineation. Different from previous fixed threshold method with over- and under-estimation issues, in ourmore » method the optimal thresholds are estimated based on cluster size and overall nightlight magnitude in the cluster, and they vary with clusters. Two large countries of United States and China with different urbanization patterns were selected to map urban extents using the proposed method. The result indicates that the urbanized area occupies about 2% of total land area in the US ranging from lower than 0.5% to higher than 10% at the state level, and less than 1% in China, ranging from lower than 0.1% to about 5% at the province level with some municipalities as high as 10%. The derived thresholds and urban extents were evaluated using high-resolution land cover data at the cluster and regional levels. It was found that our method can map urban area in both countries efficiently and accurately. Compared to previous threshold techniques, our method reduces the over- and under-estimation issues, when mapping urban extent over a large area. More important, our method shows its potential to map global urban extents and temporal dynamics using the DMSP/OLS NTL data in a timely, cost-effective way.« less

Impact of building configuration on air quality in street canyon

NASA Astrophysics Data System (ADS)

Xie, Xiaomin; Huang, Zhen; Wang, Jia-song

The objective of this study is to provide a simulation of emissions from vehicle exhausts in a street canyon within an urban environment. Standard, RNG and Chen-Kim k- ɛ turbulence models are compared with the wind tunnel measured data for optimization of turbulence model. In the first approach, the investigation is made into the effect of the different roof shapes and ambient building structures. The results indicate that the in-canyon vortex dynamics (e.g. vortex orientation) and the characteristics of pollutant dispersion are dependent on the roof shapes and ambient building structures strongly. A second set of calculations for a three-dimensional simulation of the street canyon setup was performed to investigate the influence of building geometry on pollutant dispersion. The validation of the numerical model was evaluated using an extensive experimental database obtained from the atmospheric boundary layer wind tunnel at the Meteorological Institute of Hamburg University, Germany (Studie on different roof geometries in a simplified urban environment, 1995). The studies give evidence that roof shapes, the ambient building configurations and building geometries are important factors determining the flow patterns and pollutant dispersion in street canyon.

CMAQ modeling of near-ground ozone pollution during the CAREBeijing-2006 campaign in Beijing, China

NASA Astrophysics Data System (ADS)

Wang, Xuesong; Song, Yu; Zhang, Yuanhang; Hu, Min; Zeng, Limin; Zhu, Tong

2010-05-01

The Community Multiscale Air Quality (CMAQ) modeling system, a 3-D regional chemical transport model, was used to simulate the O3 episodes during the Campaign of Air Quality Research in Beijing and surrounding areas in 2006 (CAREBeijing-2006). The model reproduced the temporal and spatial variations of the observed ozone and precursors well during the campaign. The modeling results showed the evolution of near ground O3 and the feature of vertical O3 profile on pollution days with different meteorological conditions. Process analysis was applied to investigate the contributions of local production and regional transport, and found different relative importance at different locations of Beijing. O3-NOx-VOCs sensitivity was also addressed with different precursor emission scenarios. The Beijing downtown area and downwind urban plume were usually in VOC-limited regime, whereas the upwind regions and northern mountain areas were generally characterized by NOx-sensitive chemistry. Ozone production efficiency of NOx was also calculated based on simulation results and compared with that derived from observations. For reducing O3 levels in Beijing, the above results suggest a regional emission control strategy with more emphasis on VOCs reduction in Beijing urban areas.

Seasonal progression of atmospheric particulate matter over an urban coastal region in peninsular India: Role of local meteorology and long-range transport

NASA Astrophysics Data System (ADS)

Mahapatra, P. S.; Sinha, P. R.; Boopathy, R.; Das, T.; Mohanty, S.; Sahu, S. C.; Gurjar, B. R.

2018-01-01

Measurement of particulate matter (PM) over an urban site with relatively high concentration of aerosol particles is critically important owing to its adverse health, environmental and climate impact. Here we present a 3 years' worth of measurements (January 2012 to December 2014) of PM2.5 (aerodynamic diameter of less than 2.5 μm) and PM10 (aerodynamic diameter of less than 10 μm) along with meteorological parameters and seasonal variations at Bhubaneswar an urban-coastal site, in eastern India. The concentrations of PM were determined gravimetrically from the filter samples of PM2.5 and PM10. It revealed remarkable seasonal variations with winter values (55.0 ± 23.4 μg/m3; 147.3 ± 42.4 μg/m3 for PM2.5 and PM10, respectively) about 3.5 times higher than that in pre-monsoon (15.7 ± 6.2 μg/m3; 41.8 ± 15.3 μg/m3). PM2.5 and PM10 were well correlated while PM2.5/PM10 ratios were found to be 0.38 and 0.32 during winter and pre-monsoon, indicating the predominance of coarse particles, mainly originating from long range transport of pollutants from northern and western parts of India and parts of west Asia as well. Concentration weighted trajectory (CWT) analysis revealed the IGP and North Western Odisha as the most potential sources of PM2.5 and PM10 during winter. The PM concentrations at Bhubaneswar were comparable with those at other coastal sites of India reported in the literature, but were lower than few polluted urban sites in India and Asia. Empirical model reproduced the observed seasonal variation of PM2.5 and PM10 very well over Bhubaneswar.

Characterisation of PM(10), PM(2.5) and benzene soluble organic fraction of particulate matter in an urban area of Kolkata, India.

PubMed

Gupta, A K; Nag, Subhankar; Mukhopadhyay, U K

2006-04-01

In this study, the relationship between inhalable particulate (PM(10)), fine particulate (PM(2.5)), coarse particles (PM(2.5 - 10)) and meteorological parameters such as temperature, relative humidity, solar radiation, wind speed were statistically analyzed and modelled for urban area of Kolkata during winter months of 2003-2004. Ambient air quality was monitored with a sampling frequency of twenty-four hours at three monitoring sites located near traffic intersections and in an industrial area. The monitoring sites were located 3-5 m above ground near highly trafficked and congested areas. The 24 h average PM(10) and PM(2.5) samples were collected using Thermo-Andersen high volume samplers and exposed filter papers were extracted and analysed for benzene soluble organic fraction. The ratios between PM(2.5) and PM(10) were found to be in the range of 0.6 to 0.92 and the highest ratio was found in the most polluted urban site. Statistical analysis has shown a strong positive correlation between PM(10) and PM(2.5) and inverse correlation was observed between particulate matter (PM(10) and PM(2.5)) and wind speed. Statistical analysis of air quality data shows that PM(10) and PM(2.5) are showing poor correlation with temperature, relative humidity and solar radiation. Regression equations for PM(10) and PM(2.5) and meteorological parameters were developed. The organic fraction of particulate matter soluble in benzene is an indication of poly aromatic hydrocarbon (PAH) concentration present in particulate matter. The relationship between the benzene soluble organic fraction (BSOF) of inhalable particulate (PM(10)) and fine particulate (PM(2.5)) were analysed for urban area of Kolkata. Significant positive correlation was observed between benzene soluble organic fraction of PM(10) (BSM10) and benzene soluble organic fraction of PM(2.5) (BSM2.5). Regression equations for BSM10 and BSM2.5 were developed.

Local-Rapid Evaluation of Atmospheric Conditions (L-REAC)

DTIC Science & Technology

2009-01-15

installation available 24/7 to all forms of browser-based access such as mobile blackberry browser. In 2006, the ARL presented data at an International...Oceanic and Atmospheric Administration (NOAA)/Environmental Protection Agency (EPA) Wind Tunnel study with tens-of-meter-scaled measurements sampled around...urban flow in wind tunnels , as well as articles from professional urban meteorological journals. The need to maintain a visual sensor for persons who

Urban Heat Islands

NASA Technical Reports Server (NTRS)

Luvall, Jeffrey C.; Quattrochi, Dale A.; Rickman, Doug L.; Estes, Maury G.

2011-01-01

It is estimated that by the year 2025, 80% of the world's population will live in cities. This conversion of the natural landscape vegetation into man-made urban structures such as roads and buildings drastically alter the regional surface energy budgets, hydrology, precipitation patterns, and meteorology. Research studies from many cities have documented these effects range from decreases in air quality, increased energy consumption and alteration of regional climate to direct effects on human health.

Seasonality of water quality and diarrheal disease counts in urban and rural settings in south India

NASA Astrophysics Data System (ADS)

Kulinkina, Alexandra V.; Mohan, Venkat R.; Francis, Mark R.; Kattula, Deepthi; Sarkar, Rajiv; Plummer, Jeanine D.; Ward, Honorine; Kang, Gagandeep; Balraj, Vinohar; Naumova, Elena N.

2016-02-01

The study examined relationships among meteorological parameters, water quality and diarrheal disease counts in two urban and three rural sites in Tamil Nadu, India. Disease surveillance was conducted between August 2010 and March 2012; concurrently water samples from street-level taps in piped distribution systems and from household storage containers were tested for pH, nitrate, total dissolved solids, and total and fecal coliforms. Methodological advances in data collection (concurrent prospective disease surveillance and environmental monitoring) and analysis (preserving temporality within the data through time series analysis) were used to quantify independent effects of meteorological conditions and water quality on diarrheal risk. The utility of a local calendar in communicating seasonality is also presented. Piped distribution systems in the study area showed high seasonal fluctuations in water quality. Higher ambient temperature decreased and higher rainfall increased diarrheal risk with temperature being the predominant factor in urban and rainfall in rural sites. Associations with microbial contamination were inconsistent; however, disease risk in the urban sites increased with higher median household total coliform concentrations. Understanding seasonal patterns in health outcomes and their temporal links to environmental exposures may lead to improvements in prospective environmental and disease surveillance tailored to addressing public health problems.

Does temperature nudging overwhelm aerosol radiative ...

EPA Pesticide Factsheets

For over two decades, data assimilation (popularly known as nudging) methods have been used for improving regional weather and climate simulations by reducing model biases in meteorological parameters and processes. Similar practice is also popular in many regional integrated meteorology-air quality models that include aerosol direct and indirect effects. However in such multi-modeling systems, temperature changes due to nudging can compete with temperature changes induced by radiatively active & hygroscopic short-lived tracers leading to interesting dilemmas: From weather and climate prediction’s (retrospective or future) point of view when nudging is continuously applied, is there any real added benefit of using such complex and computationally expensive regional integrated modeling systems? What are the relative sizes of these two competing forces? To address these intriguing questions, we convert temperature changes due to nudging into radiative fluxes (referred to as the pseudo radiative forcing, PRF) at the surface and troposphere, and compare the net PRF with the reported aerosol radiative forcing. Results indicate that the PRF at surface dominates PRF at top of the atmosphere (i.e., the net). Also, the net PRF is about 2-4 times larger than estimated aerosol radiative forcing at regional scales while it is significantly larger at local scales. These results also show large surface forcing errors at many polluted urban sites. Thus, operational c

Controlling Factors of Mercury Wet Deposition and Precipitation Concentrations in Upstate New York

NASA Astrophysics Data System (ADS)

Ye, Z.; Mao, H.; Driscoll, C. T.

2017-12-01

Observations from the Mercury Deposition Network (MDN) at Huntington Wildlife Forest (HWF) suggested that a significant decline in Hg concentrations in precipitation was linked to Hg emission decreases in the United States, especially in the Northeast and Midwest, and yet Hg wet deposition has remained fairly constant over the past two decades. The present study was aimed to investigate how climatic, terrestrial, and anthropogenic factors had influenced the Hg wet deposition flux in upstate New York (NY). To achieve this, an improved Community Multiscale Air Quality (CMAQ) model was employed, which included state-of-the-art Hg and halogen chemistry mechanisms. A base simulation and five sensitivity simulations were conducted. The base simulation used 2010 meteorology, U.S. EPA NEI 2011, and GEOS-Chem output as initial and boundary conditions (ICs and BCs). The five sensitivity runs each changed one condition at the time as follows: 1-3) 2004, 2005, and 2007 meteorology instead of 2010, 4) NEI 2005 Hg anthropogenic emission out of NYS instead of NEI 2011, and 5) no in-state Hg anthropogenic emission. The study period of all the simulations was March - November 2010, and the domain covered the northeastern United States at 12 km resolution. As a result, compared with rural areas in NYS, Hg wet deposition and ambient Hg concentrations in urban areas were affected more significantly by in-state anthropogenic Hg emission. The in-state anthropogenic Hg emissions contributed up to 20% of Hg wet deposition at urban sites and <1% at rural sites during the study period. Using 2005 anthropogenic Hg emissions, around twice of those in 2010, out-of-NYS emissions increased the total in-state Hg wet deposition by 2%. Hg wet deposition flux was greatly affected by meteorological conditions, causing changes varying from a 91% decrease to a factor of 5 increase in monthly accumulated wet deposition amounts. Possible affecting meteorological factors included, not limited to, solar radiation, cloud height, precipitation, wind speed and direction, and relative humidity, among which precipitation had the largest effects in most areas. Diluting effects were found in non-convective precipitation, which contributed 31-48% to changes in Hg concentration in precipitation.

Road traffic air and noise pollution exposure assessment - A review of tools and techniques.

PubMed

Khan, Jibran; Ketzel, Matthias; Kakosimos, Konstantinos; Sørensen, Mette; Jensen, Steen Solvang

2018-09-01

Road traffic induces air and noise pollution in urban environments having negative impacts on human health. Thus, estimating exposure to road traffic air and noise pollution (hereafter, air and noise pollution) is important in order to improve the understanding of human health outcomes in epidemiological studies. The aims of this review are (i) to summarize current practices of modelling and exposure assessment techniques for road traffic air and noise pollution (ii) to highlight the potential of existing tools and techniques for their combined exposure assessment for air and noise together with associated challenges, research gaps and priorities. The study reviews literature about air and noise pollution from urban road traffic, including other relevant characteristics such as the employed dispersion models, Geographic Information System (GIS)-based tool, spatial scale of exposure assessment, study location, sample size, type of traffic data and building geometry information. Deterministic modelling is the most frequently used assessment technique for both air and noise pollution of short-term and long-term exposure. We observed a larger variety among air pollution models as compared to the applied noise models. Correlations between air and noise pollution vary significantly (0.05-0.74) and are affected by several parameters such as traffic attributes, building attributes and meteorology etc. Buildings act as screens for the dispersion of pollution, but the reduction effect is much larger for noise than for air pollution. While, meteorology has a greater influence on air pollution levels as compared to noise, although also important for noise pollution. There is a significant potential for developing a standard tool to assess combined exposure of traffic related air and noise pollution to facilitate health related studies. GIS, due to its geographic nature, is well established and has a significant capability to simultaneously address both exposures. Copyright © 2018 Elsevier B.V. All rights reserved.

Urban flood return period assessment through rainfall-flood response modelling

NASA Astrophysics Data System (ADS)

Murla Tuyls, Damian; Thorndahl, Søren

2017-04-01

Intense rainfall can often cause severe floods, especially in urbanized areas, where population density or large impermeable areas are found. In this context, floods can generate a direct impact in a social-environmental-economic viewpoint. Traditionally, in design of Urban Drainage Systems (UDS), correlation between return period (RP) of a given rainfall and RP of its consequent flood has been assumed to be linear (e.g. DS/EN752 (2008)). However, this is not always the case. Complex UDS, where diverse hydraulic infrastructures are often found, increase the heterogeneity of system response, which may cause an alteration of the mentioned correlation. Consequently, reliability on future urban planning, design and resilience against floods may be also affected by this misassumption. In this study, an assessment of surface flood RP across rainfall RP has been carried out at Lystrup, a urbanized catchment area of 440ha and 10.400inhab. located in Jutland (Denmark), which has received the impact of several pluvial flooding in the last recent years. A historical rainfall dataset from the last 35 years from two different rain gauges located at 2 and 10 km from the study area has been provided by the Danish Wastewater Pollution Committee and the Danish Meteorological Institute (DMI). The most extreme 25 rainfall events have been selected through a two-step multi-criteria procedure, ensuring an adequate variability of rainfall, from extreme high peak storms with a short duration to moderate rainfall with longer duration. In addition, a coupled 1D/2D surface and network UDS model of the catchment area developed in an integrated MIKE URBAN and MIKE Flood model (DHI 2014), considering both permeable and impermeable areas, in combination with a DTM (2x2m res.) has been used to study and assess in detail flood RP. Results show an ambiguous relation between rainfall RP and flood response. Local flood levels, flood area and volume RP estimates should therefore not be neglected in order to guarantee quality of the assessment, especially in design of complex UDS, where features as the main slope, hydraulic capacity, permeability, etc. can play an important role. In addition, a novel approach has been applied to map the response time (Tc) of the flood prone areas of the system under study. Together with the flood area and volume RP estimates this provides valuable knowledge suggesting to consider the different subareas of the UDS for design purposes and to establish a robust database that allows urban areas to be resilient against the severe impact of rainfall. Acknowledgement to ERA-NET Cofund Water Works 2014 (project MUFFIN) for the partial funding of this research; to the Danish Wastewater Pollution Committee and the Danish Meteorological Institute (DMI) for providing the rainfall dataset; to the Danish Geodata Agency for providing the DTM data and to DHI for providing license to MIKE software packages. The applied model has been made available for this study by Aarhus Water Utility Services. References DHI, 2014. MIKE by DHI software package 2014. Hørsholm, DK. DS/EN 752, 2008. Drain and sewer systems outside buildings.

[Research progress and development trend of quantitative assessment techniques for urban thermal environment.

PubMed

Sun, Tie Gang; Xiao, Rong Bo; Cai, Yun Nan; Wang, Yao Wu; Wu, Chang Guang

2016-08-01

Quantitative assessment of urban thermal environment has become a focus for urban climate and environmental science since the concept of urban heat island has been proposed. With the continual development of space information and computer simulation technology, substantial progresses have been made on quantitative assessment techniques and methods of urban thermal environment. The quantitative assessment techniques have been developed to dynamics simulation and forecast of thermal environment at various scales based on statistical analysis of thermal environment on urban-scale using the historical data of weather stations. This study reviewed the development progress of ground meteorological observation, thermal infrared remote sensing and numerical simulation. Moreover, the potential advantages and disadvantages, applicability and the development trends of these techniques were also summarized, aiming to add fundamental knowledge of understanding the urban thermal environment assessment and optimization.

Assessment of ozone variations and meteorological effects in an urban area in the Mediterranean Coast.

PubMed

Dueñas, C; Fernández, M C; Cañete, S; Carretero, J; Liger, E

2002-11-01

Ozone concentrations are valuable indicators of possible health and environmental impacts. However, they are also used to monitor changes and trends in the sources of both ozone and its precursors. For this purpose, the influence of meteorological variables is a confusing factor. This study presents an analysis of a year of ozone concentrations measured in a coastal Spanish city. Firstly, the aim of this study was to perceive the daily, monthly and seasonal variation patterns of ozone concentrations. Diurnal cycles are presented by season and the fit of the data to a normal distribution is tested. In order to assess ozone behaviour under temperate weather conditions, local meteorological variables (wind direction and speed, temperature, relative humidity, pressure and rainfall) were monitored together with ozone concentrations. The main relationships we could observe in these analyses were then used to obtain a regression equation linking diurnal ozone concentrations in summer with meteorological parameters.

Long-term meteorologically independent trend analysis of ozone air quality at an urban site in the greater Houston area.

PubMed

Botlaguduru, Venkata S V; Kommalapati, Raghava R; Huque, Ziaul

2018-04-19

The Houston-Galveston-Brazoria (HGB) area of Texas has a history of ozone exceedances and is currently classified under moderate nonattainment status for the 2008 8-hr ozone standard of 75 ppb. The HGB area is characterized by intense solar radiation, high temperature, and humidity, which influence day-to-day variations in ozone concentrations. Long-term air quality trends independent of meteorological influence need to be constructed for ascertaining the effectiveness of air quality management in this area. The Kolmogorov-Zurbenko (KZ) filter technique used to separate different scales of motion in a time series, is applied in the current study for maximum daily 8-hr (MDA8) ozone concentrations at an urban site (EPA AQS Site ID: 48-201-0024, Aldine) in the HGB area. This site located within 10 miles of downtown Houston and the George Bush Intercontinental Airport, was selected for developing long-term meteorologically independent MDA8 ozone trends for the years 1990-2016. Results from this study indicate a consistent decrease in meteorologically independent MDA8 ozone between 2000-2016. This pattern could be partially attributed to a reduction in underlying NO X emissions, particularly that of lowering nitrogen dioxide (NO 2 ) levels, and a decrease in the release of highly reactive volatile organic compounds (HRVOC). Results also suggest solar radiation to be most strongly correlated to ozone, with temperature being the secondary meteorological control variable. Relative humidity and wind speed have tertiary influence at this site. This study observed that meteorological variability accounts for a high of 61% variability in baseline ozone (low-frequency component, sum of long-term and seasonal components), while 64% of the change in long-term MDA8 ozone post-2000 could be attributed to NO X emissions reduction. Long-term MDA8 ozone trend component was estimated to be decreasing at a linear rate of 0.412 ± 0.007 ppb/yr for the years 2000-2016, and 0.155 ± 0.005 ppb/yr for the overall period of 1990-2016. Implications Statement The effectiveness of air emission controls can be evaluated by developing long-term air quality trends independent of meteorological influences. KZ filter technique is a well-established method to separate an air quality time-series into: short-term, seasonal and long-term components. This paper applies the KZ filter technique to MDA8 ozone data between 1990-2016 at an urban site in the Greater Houston area and estimates the variance accounted for, by the primary meteorological control variables. Estimates for linear trends of MDA8 ozone are calculated and underlying causes are investigated to provide a guidance for further investigation into air quality management of the Greater Houston Area.

CO2 Urban Synthesis and Analysis ("CO2-USA") Network

NASA Astrophysics Data System (ADS)

Lin, J. C.; Hutyra, L.; Loughner, C.; Stein, A. F.; Lusk, K.; Mitchell, L.; Gately, C.; Wofsy, S. C.

2017-12-01

Emissions of carbon associated with cities comprise a large component of the anthropogenic source. A number of cities have announced plans to reduce greenhouse gas emissions, but the scientific knowledge to quantitatively track emissions and assess the efficacy of mitigation is lacking. As the global population increasingly resides in urban regions, scientific knowledge about how much, where, and why a particular city emits carbon becomes increasingly important. To address this gap, researchers have initiated studies of carbon emissions and cycling in several U.S. cities, making it timely to develop a collaborative network to exchange information on community standards and common measurements, facilitate data sharing, and create analysis frameworks and cross-city syntheses to catalyze a new generation of researchers and enable new collaborations tackling important objectives that are difficult to address in isolation. We describe initial results from an incipient network focusing initially on cities in the U.S. with low barriers of entry that entrains a cross-section of U.S. urban centers with varying characteristics: size, population density, vegetation, urban form, infrastructure, development rates, climate, and meteorological patterns. Results will be reported that emerge from an initial workshop covering data harmonization & integration, inventory comparison, stakeholder outreach, network design, inverse modeling, and collaboration.

Network design for quantifying urban CO 2 emissions: assessing trade-offs between precision and network density

DOE PAGES

Turner, Alexander J.; Shusterman, Alexis A.; McDonald, Brian C.; ...

2016-11-01

The majority of anthropogenic CO 2 emissions are attributable to urban areas. While the emissions from urban electricity generation often occur in locations remote from consumption, many of the other emissions occur within the city limits. Evaluating the effectiveness of strategies for controlling these emissions depends on our ability to observe urban CO 2 emissions and attribute them to specific activities. Cost-effective strategies for doing so have yet to be described. Here we characterize the ability of a prototype measurement network, modeled after the Berkeley Atmospheric CO 2 Observation Network (BEACO 2N) in California's Bay Area, in combination with anmore » inverse model based on the coupled Weather Research and Forecasting/Stochastic Time-Inverted Lagrangian Transport (WRF-STILT) to improve our understanding of urban emissions. The pseudo-measurement network includes 34 sites at roughly 2 km spacing covering an area of roughly 400 km 2. The model uses an hourly 1 × 1 km 2 emission inventory and 1 × 1 km 2 meteorological calculations. We perform an ensemble of Bayesian atmospheric inversions to sample the combined effects of uncertainties of the pseudo-measurements and the model. We vary the estimates of the combined uncertainty of the pseudo-observations and model over a range of 20 to 0.005 ppm and vary the number of sites from 1 to 34. We use these inversions to develop statistical models that estimate the efficacy of the combined model–observing system in reducing uncertainty in CO 2 emissions. We examine uncertainty in estimated CO 2 fluxes on the urban scale, as well as for sources embedded within the city such as a line source (e.g., a highway) or a point source (e.g., emissions from the stacks of small industrial facilities). Using our inversion framework, we find that a dense network with moderate precision is the preferred setup for estimating area, line, and point sources from a combined uncertainty and cost perspective. The dense network considered here (modeled after the BEACO 2N network with an assumed mismatch error of 1 ppm at an hourly temporal resolution) could estimate weekly CO 2 emissions from an urban region with less than 5 % error, given our characterization of the combined observation and model uncertainty.« less

Network design for quantifying urban CO 2 emissions: assessing trade-offs between precision and network density

DOE Office of Scientific and Technical Information (OSTI.GOV)

Turner, Alexander J.; Shusterman, Alexis A.; McDonald, Brian C.

The majority of anthropogenic CO 2 emissions are attributable to urban areas. While the emissions from urban electricity generation often occur in locations remote from consumption, many of the other emissions occur within the city limits. Evaluating the effectiveness of strategies for controlling these emissions depends on our ability to observe urban CO 2 emissions and attribute them to specific activities. Cost-effective strategies for doing so have yet to be described. Here we characterize the ability of a prototype measurement network, modeled after the Berkeley Atmospheric CO 2 Observation Network (BEACO 2N) in California's Bay Area, in combination with anmore » inverse model based on the coupled Weather Research and Forecasting/Stochastic Time-Inverted Lagrangian Transport (WRF-STILT) to improve our understanding of urban emissions. The pseudo-measurement network includes 34 sites at roughly 2 km spacing covering an area of roughly 400 km 2. The model uses an hourly 1 × 1 km 2 emission inventory and 1 × 1 km 2 meteorological calculations. We perform an ensemble of Bayesian atmospheric inversions to sample the combined effects of uncertainties of the pseudo-measurements and the model. We vary the estimates of the combined uncertainty of the pseudo-observations and model over a range of 20 to 0.005 ppm and vary the number of sites from 1 to 34. We use these inversions to develop statistical models that estimate the efficacy of the combined model–observing system in reducing uncertainty in CO 2 emissions. We examine uncertainty in estimated CO 2 fluxes on the urban scale, as well as for sources embedded within the city such as a line source (e.g., a highway) or a point source (e.g., emissions from the stacks of small industrial facilities). Using our inversion framework, we find that a dense network with moderate precision is the preferred setup for estimating area, line, and point sources from a combined uncertainty and cost perspective. The dense network considered here (modeled after the BEACO 2N network with an assumed mismatch error of 1 ppm at an hourly temporal resolution) could estimate weekly CO 2 emissions from an urban region with less than 5 % error, given our characterization of the combined observation and model uncertainty.« less

Comparing emission rates derived from a model with a plume-based approach and quantifying the contribution of vehicle classes to on-road emissions and air quality.

PubMed

Xu, Junshi; Wang, Jonathan; Hilker, Nathan; Fallah-Shorshani, Masoud; Saleh, Marc; Tu, Ran; Wang, An; Minet, Laura; Stogios, Christos; Evans, Greg; Hatzopoulou, Marianne

2018-06-05

This study presents a comparison of fleet averaged emission factors (EFs) derived from a traffic emission model with EFs estimated using plume-based measurements, including an investigation of the contribution of vehicle classes to carbon monoxide (CO), nitrogen oxides (NO x ), and elemental carbon (EC) along an urban corridor. To this end, a field campaign was conducted over one week in June 2016 on an arterial road in Toronto, Canada. Traffic data were collected using a traffic camera and a radar, while air quality was characterized using two monitoring stations: one located at ground-level and another at the rooftop of a four-storey building. A traffic simulation model was calibrated and validated and sec-by-sec speed profiles for all vehicle trajectories were extracted to model emissions. In addition, dispersion modelling was conducted to identify the extent to which differences in emissions translate to differences in near-road concentrations. Our results indicate that modelled EFs for CO and NO x are twice as high as plume-based EFs. Besides, modelled results indicate that transit bus emissions accounted for 60% and 70% of the total emissions of NO x and EC. Transit bus emission rates in g/passenger.km for NO x and EC were up to 8 and 22 times the emission rates of passenger cars. In contrast, the Toronto streetcars, which are electrically fuelled, were found to improve near-road air quality despite their negative impact on traffic speeds. Finally, we observe that the difference in estimated concentrations derived from the two methods is not as large as the difference in estimated emissions due to the influence of meteorology and of the urban background given that the study network is located in a busy downtown area. Implications This study presents a comparison of fleet averaged emission factors (EFs) derived from a traffic emission model with EFs estimated using plume-based measurements, including an investigation of the contribution of vehicle classes to various pollutants. Besides, dispersion modelling was conducted to identify the extent to which differences in emissions translate to differences in near-road concentrations. We observe that the difference in estimated concentrations derived from the two methods is not as large as the difference in estimated emissions due to the influence of meteorology and of the urban background as the study network is located in a busy downtown area.

Impact analysis of traffic-related air pollution based on real-time traffic and basic meteorological information.

PubMed

Pan, Long; Yao, Enjian; Yang, Yang

2016-12-01

With the rapid development of urbanization and motorization in China, traffic-related air pollution has become a major component of air pollution which constantly jeopardizes public health. This study proposes an integrated framework for estimating the concentration of traffic-related air pollution with real-time traffic and basic meteorological information and also for further evaluating the impact of traffic-related air pollution. First, based on the vehicle emission factor models sensitive to traffic status, traffic emissions are calculated according to the real-time link-based average traffic speed, traffic volume, and vehicular fleet composition. Then, based on differences in meteorological conditions, traffic pollution sources are divided into line sources and point sources, and the corresponding methods to determine the dynamic affecting areas are also proposed. Subsequently, with basic meteorological data, Gaussian dispersion model and puff integration model are applied respectively to estimate the concentration of traffic-related air pollution. Finally, the proposed estimating framework is applied to calculate the distribution of CO concentration in the main area of Beijing, and the population exposure is also calculated to evaluate the impact of traffic-related air pollution on public health. Results show that there is a certain correlation between traffic indicators (i.e., traffic speed and traffic intensity) of the affecting area and traffic-related CO concentration of the target grid, which indicates the methods to determine the affecting areas are reliable. Furthermore, the reliability of the proposed estimating framework is verified by comparing the predicted and the observed ambient CO concentration. In addition, results also show that the traffic-related CO concentration is higher in morning and evening peak hours, and has a heavier impact on public health within the Fourth Ring Road of Beijing due to higher population density and higher CO concentration under calm wind condition in this area. Copyright © 2016 Elsevier Ltd. All rights reserved.

Presenting SAPUSS: Solving Aerosol Problem by Using Synergistic Strategies in Barcelona, Spain

NASA Astrophysics Data System (ADS)

Dall'Osto, M.; Querol, X.; Alastuey, A.; Minguillon, M. C.; Alier, M.; Amato, F.; Brines, M.; Cusack, M.; Grimalt, J. O.; Karanasiou, A.; Moreno, T.; Pandolfi, M.; Pey, J.; Reche, C.; Ripoll, A.; Tauler, R.; Van Drooge, B. L.; Viana, M.; Harrison, R. M.; Gietl, J.; Beddows, D.; Bloss, W.; O'Dowd, C.; Ceburnis, D.; Martucci, G.; Ng, N. L.; Worsnop, D.; Wenger, J.; Mc Gillicuddy, E.; Sodeau, J.; Healy, R.; Lucarelli, F.; Nava, S.; Jimenez, J. L.; Gomez Moreno, F.; Artinano, B.; Prévôt, A. S. H.; Pfaffenberger, L.; Frey, S.; Wilsenack, F.; Casabona, D.; Jiménez-Guerrero, P.; Gross, D.; Cots, N.

2013-09-01

This paper presents the summary of the key objectives, instrumentation and logistic details, goals, and initial scientific findings of the European Marie Curie Action SAPUSS project carried out in the western Mediterranean Basin (WMB) during September-October in autumn 2010. The key SAPUSS objective is to deduce aerosol source characteristics and to understand the atmospheric processes responsible for their generations and transformations - both horizontally and vertically in the Mediterranean urban environment. In order to achieve so, the unique approach of SAPUSS is the concurrent measurements of aerosols with multiple techniques occurring simultaneously in six monitoring sites around the city of Barcelona (NE Spain): a main road traffic site, two urban background sites, a regional background site and two urban tower sites (150 m and 545 m above sea level, 150 m and 80 m above ground, respectively). SAPUSS allows us to advance our knowledge sensibly of the atmospheric chemistry and physics of the urban Mediterranean environment. This is well achieved only because of both the three dimensional spatial scale and the high sampling time resolution used. During SAPUSS different meteorological regimes were encountered, including warm Saharan, cold Atlantic, wet European and stagnant regional ones. The different meteorology of such regimes is herein described. Additionally, we report the trends of the parameters regulated by air quality purposes (both gaseous and aerosol mass concentrations); and we also compare the six monitoring sites. High levels of traffic-related gaseous pollutants were measured at the urban ground level monitoring sites, whereas layers of tropospheric ozone were recorded at tower levels. Particularly, tower level night-time average ozone concentrations (80 ± 25 μg m-3) were up to double compared to ground level ones. The examination of the vertical profiles clearly shows the predominant influence of NOx on ozone concentrations, and a source of ozone aloft. Analysis of the particulate matter (PM) mass concentrations shows an enhancement of coarse particles (PM2.5-10) at the urban ground level (+64%, average 11.7 μg m-3) but of fine ones (PM1) at urban tower level (+28%, average 14.4 μg m-3). These results show complex dynamics of the size-resolved PM mass at both horizontal and vertical levels of the study area. Preliminary modelling findings reveal an underestimation of the fine accumulation aerosols. In summary, this paper lays the foundation of SAPUSS, an integrated study of relevance to many other similar urban Mediterranean coastal environment sites.

Fine Particulate Matter Predictions Using High Resolution Aerosol Optical Depth (AOD) Retrievals

NASA Technical Reports Server (NTRS)

Chudnovsky, Alexandra A.; Koutrakis, Petros; Kloog, Itai; Melly, Steven; Nordio, Francesco; Lyapustin, Alexei; Wang, Jujie; Schwartz, Joel

2014-01-01

To date, spatial-temporal patterns of particulate matter (PM) within urban areas have primarily been examined using models. On the other hand, satellites extend spatial coverage but their spatial resolution is too coarse. In order to address this issue, here we report on spatial variability in PM levels derived from high 1 km resolution AOD product of Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm developed for MODIS satellite. We apply day-specific calibrations of AOD data to predict PM(sub 2.5) concentrations within the New England area of the United States. To improve the accuracy of our model, land use and meteorological variables were incorporated. We used inverse probability weighting (IPW) to account for nonrandom missingness of AOD and nested regions within days to capture spatial variation. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance among others. Out-of-sample "ten-fold" cross-validation was used to quantify the accuracy of model predictions. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations, with out-of- sample R(sub 2) of 0.89. Furthermore, our study shows that the model captures the pollution levels along highways and many urban locations thereby extending our ability to investigate the spatial patterns of urban air quality, such as examining exposures in areas with high traffic. Our results also show high accuracy within the cities of Boston and New Haven thereby indicating that MAIAC data can be used to examine intra-urban exposure contrasts in PM(sub 2.5) levels.

Air Pollutant Distribution and Mesoscale Circulation Systems During Escompte

NASA Astrophysics Data System (ADS)

Kottmeier, Ch.; Kalthoff, N.; Corsmeier, U.; Robin, D.; Thürauf, J.; Hofherr, T.; Hasel, M.

The distribution of pollutants observed with an Dornier 128 instrumented aircraft and from AIRMARAIX ground stations during one day of the Escompte experiment (June 25, 2001) is analysed in relation to the mesoscale wind systems and vertical mixing from aircraft and radiosonde data. The ESCOMPTE-experiment (http://medias.obs- mip.fr/escompte) was carried out in June and July 2001 in the urban area of Marseille and its rural surroundings to investigate periods with photosmog conditions. The over- all aim is to produce an appropriate high quality 3-D data set which includes emission, meteorological, and chemical data. The data is used for the validation of mesoscale models and for chemical and meteorological process studies. The evolution of pho- tosmog episodes with high ozone concentrations depends on both chemical transfor- mation processes and meteorological conditions. As Marseille is situated between the Mediterranean Sea in the south and mountainous sites in the north, under weak large- scale flow the meteorological conditions are dominated by thermally driven circula- tion systems which strongly influence the horizontal transport of air pollutants. Ad- ditionally, vertically exchange processes like mountain venting and slope winds may contribute in the temporal evolution of the trace gas concentration of the city plume in the atmospheric boundary layer and are particularly studied by the Dornier flight measurements. Therefore the experiment was designed to measure both, the chemi- cal species and meteorological parameters with high resolution in space and time by surface stations, aircraft and vertical profiling systems like radiosondes, sodars and lidars. Results are shown (a) on the evolution of the wind field and the ozone concen- trations during June 25, when an ozone maximum develops about 60 km in the lee site of Marseille and (b) the vertical transport of air pollutants between the boundary layer and the free troposphere.

Influences of natural emission sources (wildfires and Saharan dust) on the urban organic aerosol in Barcelona (Western Mediterranean Basis) during a PM event.

PubMed

van Drooge, Barend L; Lopez, Jordi F; Grimalt, Joan O

2012-11-01

The urban air quality in Barcelona in the Western Mediterranean Basin is characterized by overall high particulate matter (PM) concentrations, due to intensive local anthropogenic emissions and specific meteorological conditions. Moreover, on several days, especially in summer, natural PM sources, such as long-range transported Saharan dust from Northern Africa or wildfires on the Iberian Peninsula and around the Mediterranean Basin, may influence the levels and composition of the organic aerosol. In the second half of July 2009, daily collected PM(10) filter samples in an urban background site in Barcelona were analyzed on organic tracer compounds representing several emission sources. During this period, an important PM peak event was observed. Individual organic compound concentrations increased two to five times during this event. Although highest increase was observed for the organic tracer of biomass burning, the contribution to the organic aerosol was estimated to be around 6 %. Organic tracers that could be related to Saharan dust showed no correlation with the PM and OC levels, while this was the case for those related to fossil fuel combustion from traffic emissions. Moreover, a change in the meteorological conditions gave way to an overall increase of the urban background contamination. Long-range atmospheric transport of organic compounds from primary emissions sources (i.e., wildfires and Saharan dust) has a relatively moderate impact on the organic aerosol in an urban area where the local emissions are dominating.

Project ATLANTA (ATlanta Land-use ANalysis: Temperature and Air quality): A Study of how the Urban Landscape Affects Meteorology and Air Quality Through Time

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.; Estes, Maurice G.; Lo, C. P.; Kidder, Stanley Q.; Hafner, Jan; Taha, Haider; Bornstein, Robert D.; Gillies, Robert R.; Gallo, Kevin P.

1998-01-01

It is our intent through this investigation to help facilitate measures that can be Project ATLANTA (ATlanta Land-use ANalysis: applied to mitigate climatological or air quality Temperature and Air-quality) is a NASA Earth degradation, or to design alternate measures to sustain Observing System (EOS) Interdisciplinary Science or improve the overall urban environment in the future. investigation that seeks to observe, measure, model, and analyze how the rapid growth of the Atlanta. The primary objectives for this research effort are: 1) To In the last half of the 20th century, Atlanta, investigate and model the relationship between Atlanta Georgia has risen as the premier commercial, urban growth, land cover change, and the development industrial, and transportation urban area of the of the urban heat island phenomenon through time at southeastern United States. The rapid growth of the nested spatial scales from local to regional; 2) To Atlanta area, particularly within the last 25 years, has investigate and model the relationship between Atlanta made Atlanta one of the fastest growing metropolitan urban growth and land cover change on air quality areas in the United States. The population of the through time at nested spatial scales from local to Atlanta metropolitan area increased 27% between 1970 regional; and 3) To model the overall effects of urban and 1980, and 33% between 1980-1990 (Research development on surface energy budget characteristics Atlanta, Inc., 1993). Concomitant with this high rate of across the Atlanta urban landscape through time at population growth, has been an explosive growth in nested spatial scales from local to regional. Our key retail, industrial, commercial, and transportation goal is to derive a better scientific understanding of how services within the Atlanta region. This has resulted in land cover changes associated with urbanization in the tremendous land cover change dynamics within the Atlanta area, principally in transforming forest lands to metropolitan region, wherein urbanization has urban land covers through time, has, and will, effect consumed vast acreas of land adjacent to the city local and regional climate, surface energy flux, and air proper and has pushed the rural/urban fringe farther quality characteristics. Allied with this goal is the and farther away from the original Atlanta urban core. prospect that the results from this research can be An enormous transition of land from forest and applied by urban planners, environmental managers agriculture to urban land uses has occurred in the and other decision-makers, for determining how Atlanta area in the last 25 years, along with subsequent urbanization has impacted the climate and overall

Comprehensive evaluation of multi-year real-time air quality forecasting using an online-coupled meteorology-chemistry model over southeastern United States

NASA Astrophysics Data System (ADS)

Zhang, Yang; Hong, Chaopeng; Yahya, Khairunnisa; Li, Qi; Zhang, Qiang; He, Kebin

2016-08-01

An online-coupled meteorology-chemistry model, WRF/Chem-MADRID, has been deployed for real time air quality forecast (RT-AQF) in southeastern U.S. since 2009. A comprehensive evaluation of multi-year RT-AQF shows overall good performance for temperature and relative humidity at 2-m (T2, RH2), downward surface shortwave radiation (SWDOWN) and longwave radiation (LWDOWN), and cloud fraction (CF), ozone (O3) and fine particles (PM2.5) at surface, tropospheric ozone residuals (TOR) in O3 seasons (May-September), and column NO2 in winters (December-February). Moderate-to-large biases exist in wind speed at 10-m (WS10), precipitation (Precip), cloud optical depth (COT), ammonium (NH4+), sulfate (SO42-), and nitrate (NO3-) from the IMPROVE and SEARCH networks, organic carbon (OC) at IMPROVE, and elemental carbon (EC) and OC at SEARCH, aerosol optical depth (AOD) and column carbon monoxide (CO), sulfur dioxide (SO2), and formaldehyde (HCHO) in both O3 and winter seasons, column nitrogen dioxide (NO2) in O3 seasons, and TOR in winters. These biases indicate uncertainties in the boundary layer and cloud process treatments (e.g., surface roughness, microphysics cumulus parameterization), emissions (e.g., O3 and PM precursors, biogenic, mobile, and wildfire emissions), upper boundary conditions for all major gases and PM2.5 species, and chemistry and aerosol treatments (e.g., winter photochemistry, aerosol thermodynamics). The model shows overall good skills in reproducing the observed multi-year trends and inter-seasonal variability in meteorological and radiative variables such as T2, WS10, Precip, SWDOWN, and LWDOWN, and relatively well in reproducing the observed trends in surface O3 and PM2.5, but relatively poor in reproducing the observed column abundances of CO, NO2, SO2, HCHO, TOR, and AOD. The sensitivity simulations using satellite-constrained boundary conditions for O3 and CO show substantial improvement for both spatial distribution and domain-mean performance statistics. The model's forecasting skills for air quality can be further enhanced through improving model inputs (e.g., anthropogenic emissions for urban areas and upper boundary conditions of chemical species), meteorological forecasts (e.g., WS10, Precip) and meteorologically-dependent emissions (e.g., biogenic and wildfire emissions), and model physics and chemical treatments (e.g., gas-phase chemistry in winter conditions, cloud processes and their interactions with radiation and aerosol).

An hourly regression model for ultrafine particles in a near-highway urban area

PubMed Central

Patton, Allison P.; Collins, Caitlin; Naumova, Elena N.; Zamore, Wig; Brugge, Doug; Durant, John L.

2015-01-01

Estimating ultrafine particle number concentrations (PNC) near highways for exposure assessment in chronic health studies requires models capable of capturing PNC spatial and temporal variations over the course of a full year. The objectives of this work were to describe the relationship between near-highway PNC and potential predictors, and to build and validate hourly log-linear regression models. PNC was measured near Interstate 93 (I-93) in Somerville, MA (USA) using a mobile monitoring platform driven for 234 hours on 43 days between August 2009 and September 2010. Compared to urban background, PNC levels were consistently elevated within 100–200 m of I-93, with gradients impacted by meteorological and traffic conditions. Temporal and spatial variables including wind speed and direction, temperature, highway traffic, and distance to I-93 and major roads contributed significantly to the full regression model. Cross-validated model R2 values ranged from 0.38–0.47, with higher values achieved (0.43–0.53) when short-duration PNC spikes were removed. The model predicts highest PNC near major roads and on cold days with low wind speeds. The model allows estimation of hourly ambient PNC at 20-m resolution in a near-highway neighborhood. PMID:24559198

Ozone production during an urban air stagnation episode over Nashville, Tennessee

NASA Astrophysics Data System (ADS)

Valente, R. J.; Imhoff, R. E.; Tanner, R. L.; Meagher, J. F.; Daum, P. H.; Hardesty, R. M.; Banta, R. M.; Alvarez, R. J.; McNider, R. T.; Gillani, N. V.

1998-09-01

The highest O3 levels observed during the 1995 Southern Oxidants Study in middle Tennessee occurred during a period of air stagnation from July 11 through July 15. Extensive airborne (two fixed wing and one helicopter) and ground-based measurements of the chemistry and meteorology of this episode near Nashville, Tennessee, are presented. In situ airborne measurements include O3, NOy, NO, NO2, SO2, CO, nitrate, hydrocarbons, and aldehydes. Airborne LIDAR O3 measurements are also utilized to map the vertical and horizontal extent of the urban plume. The use of multiple instrumented research aircraft permitted highly detailed mapping of the plume chemistry in the vertical and horizontal dimensions. Interactions between the urban Nashville plume (primarily a NOx and hydrocarbon source) and the Gallatin coal-fired power plant plume (primarily a NOx and SO2 source) are also documented, and comparisons of ozone formation in the isolated and mixed urban and power plant plume are presented. The data suggest that during this episode the background air and the edges of the urban plume are NOx sensitive and the core of the urban plume is hydrocarbon sensitive. Under these worst case meteorological conditions, ambient O3 levels well over the level of the new National Ambient Air Quality Standard (NAAQS) for ozone (80 ppb) were observed over and just downwind of Nashville. For example, on July 12, the boundary layer air upwind of Nashville showed 60 to 70 ppb O3, while just downwind of the city the urban plume maximum was over 140 ppb O3. With a revised ozone standard set at 80 ppb (8 hour average) and upwind levels already within 10 or 20 ppb of the standard, only a slight increase in ozone from the urban area will cause difficulty in attaining the standard at monitors near the core of the urban plume during this type of episode. The helicopter mapping and LIDAR aircraft data clearly illustrate that high O3 levels can occur during stagnation episodes within a few kilometers of and even within the urban area. The extremely light boundary layer winds (1-3 m s-1) contributed to the creation of an ozone dome or blob which stayed very near to the city rather than an elongated plume. The small spatial scale of the zone of high O3 concentrations is mapped in detail demonstrating that the regulatory monitoring network failed to document the maximum O3 concentrations. Modelers using such regulatory data to test photochemical algorithms need to bear in mind that magnitude and frequency of urban ozone may be underestimated by monitoring networks, especially in medium-sized urban areas under slow transport conditions. Finally, this effort shows the value of collaborative field measurements from multiple platforms in developing a more complete picture of the chemistry and transport of photochemical O3.

The POLIMI forecasting chain for real time flood and drought predictions

NASA Astrophysics Data System (ADS)

Ceppi, Alessandro; Ravazzani, Giovanni; Corbari, Chiara; Mancini, Marco

2016-04-01

Nowadays coupling meteorological and hydrological models is recognized by scientific community as a necessary way to forecast extreme hydrological phenomena, in order to activate useful mitigation measurements and alert systems in advance. The development and implementation of a real-time forecasting chain with a hydro-meteorological operational alert procedure for flood and drought events is presented in this study. Different weather models are used to build the POLIMI operative chain: the probabilistic COSMO-LEPS model with 16 ensembles developed by ARPA-Emilia Romagna, the deterministic Bolam and Moloch models, developed by the Italian ISAC-CNR, and nine further simulations obtained by different runs of the WRF-ARW (3), WRF-NMM (2), ETA2012 (1) and the GFS (3), provided by the private Epson Meteo Center and Terraria companies. All the meteorological runs are then implemented with the rainfall-runoff physically-based distributed FEST-WB model, developed at Politecnico di Milano to obtain a multi-model approach system with hydrological ensemble forecasts in different areas of study over the Italian country. As far as concerning drought predictions, three test-beds are monitored: two in maize fields, one in the Puglia region (South of Italy), and another in the Po Valley area, (northern Italy), and one in a golf course in Milan city. The hydrological model was here calibrated and validated against measurements of latent heat flux and soil moisture acquired by an eddy-covariance station, TDR probes and remote sensing images. Regarding flood forecasts, two test-sites are chosen: the first one is the urban area northern Milan where three catchments (the Seveso, Olona, and Lambro River basins) are used to show how early warning systems are an effective complement to structural measures for flood control in Milan city which flooded frequently in the last 25 years, while the second test-site is the Idro Lake, located between the Lombardy and Trentino region where the POLIMI hydro-meteorological chain is performed to forecast the hydrometric lake level for a better management of the upstream and downstream basin. The same hydrological model has been here calibrated and validated with observed data coming from local bodies: ARPA Lombardy, Meteonetwork and Meteo Trentino. Reliability of the forecasting system and its benefits are assessed with skill scores on some cases-study occurred in the recent years and through the real-time visualization of the implemented dashboards.

Aircraft observations of the urban CO2 dome in London and calculated daytime CO2 fluxes at the urban-regional scale

NASA Astrophysics Data System (ADS)

Font, Anna; Morgui, Josep Anton; Grimmond, Sue; Barratt, Benjamin

2013-04-01

Traffic, industry and energy production and consumption within urban boundaries emit great amounts of CO2 into the atmosphere, creating an urban increment of CO2 mixing ratios compared to the surrounding rural atmosphere. Monitoring CO2 within these 'urban domes' has been proposed as a means to evaluate the effectiveness of policies aiming to mitigate and reduce CO2 urban emissions (CMEGGE, 2010). London is the biggest urban conurbation in Western Europe with more than 8 million inhabitants, and it emitted roughly 45000 ktn CO2 in 2010 (DECC, 2012). In order to develop and implement observational strategies to measure the contribution of urban areas into the global carbon cycle, two airborne surveys were deployed using the Natural and Environment Research Council - Airborne Research and Survey Facility (NERC-ARSF). High frequency measurements of atmospheric CO2, O3, particles and meteorological variables were taken over London in October 2011 and July 2012. CO2 mixing ratios were measured by a Non-Dispersive IR instrument developed by AOS. In July 2012, a Cavity Ring-Down Spectroscopy (CDRS) instrument developed by PICARRO was deployed measuring CO2, CH4 and water vapour at 1Hz resolution. The objectives of the campaigns were to measure the CO2 dome over London and to calculate CO2 emissions at the urban-regional-scale. London was crossed by two transects (SW-NE and SSE-NNW) at an altitude of 360 m and vertical profiles up to 2000 m were carried out to characterize the structure of the atmosphere. Aircraft measurements allowed observation on how CO2 domes were shaped by meteorological conditions. In October 2011, the mean CO2 mixing ratio measured in London was on average 2 ppmv higher than the suburban measurements within the boundary layer. However, under low wind speeds, the CO2 mixing ratio in the urban mixing ratio peaked in central London (>10 ppmv) and decreased towards the city boundaries. Under windy conditions, the structure of the urban dome was dispersed downwind, with peak concentrations displaced from the urban centre along the main wind direction. The urban-regional surface CO2 flux was calculated for four days in October 2011 by either the Integrative Mass Boundary Layer (IMBL) or the Column Integration method (CIM), dependent on meteorological conditions. The diurnal CO2 flux in London obtained from the aircraft observations ranged from 36 to 71 μmol CO2 m-2 s-1 during the day time. This compared well with continuous measurements of CO2 exchange by an eddy-covariance system located in central London. The day-to-day variability observed in the calculated CO2 fluxes responded to the spatial variability of the influence area and emissions that observations were sensitive to. This study provides an example how aircraft surveys in urban areas can be used to estimate CO2 surface fluxes at the urban-regional scale. It also presents an important cross-validation of two independent measurement-based methods to infer the contribution of urban areas to climate change in terms of CO2 emissions that complement bottom-up emissions inventories. References Committee on Methods for Estimating Greenhouse Gas Emissions (2010), The National Academia Press. DECC (2012), http://www.decc.gov.uk/en/content/cms/statistics/indicators/ni186/ni186.aspx

Non Urban Troposphere Composition Symposium, Hollywood, Fla., November 10-12, 1976, Proceedings

NASA Technical Reports Server (NTRS)

1977-01-01

Papers are presented which originate from a conference on 'The Non-Urban Troposphere Composition', held in 1976. Attention is given to distributions of nitrous oxide in the atmosphere, and to tropospheric and stratospheric compositions which are perturbed by NO(x) emissions from high-altitude aircraft. Ozone is studied in terms of in situ measurements; various meteorological analyses of tropopause folding, ozone measurements in the Boston area, and ozone measurements in rural areas are presented. A one-dimensional model used to study tropospheric photochemistry numerically is presented as are vertical profiles of tropospheric and stratospheric molecular hydrogen. The oxidation of ammonia, methane, and hydrogen sulfide is assessed in nonurban tropospheres along with nonurban measurements of ethane and methane for various atmospheric conditions. With reference to the particle size distribution of chloride in the marine aerosol, organic and inorganic chlorine concentrations are evaluated, and measurements of sea-air CO2 flux by eddy correlation are investigated.

Effect of VOC emissions from vegetation on urban air quality during hot periods

NASA Astrophysics Data System (ADS)

Churkina, Galina; Kuik, Friderike; Bonn, Boris; Lauer, Axel; Grote, Ruediger; Butler, Tim

2016-04-01

Programs to plant millions of trees in cities around the world aim at the reduction of summer temperatures, increase of carbon storage, storm water control, and recreational space, as well as at poverty alleviation. These urban greening programs, however, do not take into account how closely human and natural systems are coupled in urban areas. Compared with the surroundings of cities, elevated temperatures together with high anthropogenic emissions of air and water pollutants are quite typical in urban systems. Urban and sub-urban vegetation respond to changes in meteorology and air quality and can react to pollutants. Neglecting this coupling may lead to unforeseen negative effects on air quality resulting from urban greening programs. The potential of emissions of volatile organic compounds (VOC) from vegetation combined with anthropogenic emissions of air pollutants to produce ozone has long been recognized. This ozone formation potential increases under rising temperatures. Here we investigate how emissions of VOC from urban vegetation affect corresponding ground-level ozone and PM10 concentrations in summer and especially during heat wave periods. We use the Weather Research and Forecasting Model with coupled atmospheric chemistry (WRF-CHEM) to quantify these feedbacks in the Berlin-Brandenburg region, Germany during the two summers of 2006 (heat wave) and 2014 (reference period). VOC emissions from vegetation are calculated by MEGAN 2.0 coupled online with WRF-CHEM. Our preliminary results indicate that the contribution of VOCs from vegetation to ozone formation may increase by more than twofold during heat wave periods. We highlight the importance of the vegetation for urban areas in the context of a changing climate and discuss potential tradeoffs of urban greening programs.

A validated methodology for the prediction of heating and cooling energy demand for buildings within the Urban Heat Island: Case-study of London

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kolokotroni, Maria; Bhuiyan, Saiful; Davies, Michael

2010-12-15

This paper describes a method for predicting air temperatures within the Urban Heat Island at discreet locations based on input data from one meteorological station for the time the prediction is required and historic measured air temperatures within the city. It uses London as a case-study to describe the method and its applications. The prediction model is based on Artificial Neural Network (ANN) modelling and it is termed the London Site Specific Air Temperature (LSSAT) predictor. The temporal and spatial validity of the model was tested using data measured 8 years later from the original dataset; it was found thatmore » site specific hourly air temperature prediction provides acceptable accuracy and improves considerably for average monthly values. It thus is a very reliable tool for use as part of the process of predicting heating and cooling loads for urban buildings. This is illustrated by the computation of Heating Degree Days (HDD) and Cooling Degree Hours (CDH) for a West-East Transect within London. The described method could be used for any city for which historic hourly air temperatures are available for a number of locations; for example air pollution measuring sites, common in many cities, typically measure air temperature on an hourly basis. (author)« less

Investigations of environmental effects on freeway acoustics.

DOT National Transportation Integrated Search

2010-03-01

The study reported here was designed to examine the impact of background meteorological conditions on the : propagation of noise from urban freeways in the Phoenix area. The aim was to understand and predict how : sound waves emanating from highways ...

CO2 dispersion modelling over Paris region within the CO2-MEGAPARIS project

NASA Astrophysics Data System (ADS)

Lac, C.; Donnelly, R. P.; Masson, V.; Pal, S.; Riette, S.; Donier, S.; Queguiner, S.; Tanguy, G.; Ammoura, L.; Xueref-Remy, I.

2013-05-01

Accurate simulation of the spatial and temporal variability of tracer mixing ratios over urban areas is a challenging and interesting task needed to be performed in order to utilise CO2 measurements in an atmospheric inverse framework and to better estimate regional CO2 fluxes. This study investigates the ability of a high-resolution model to simulate meteorological and CO2 fields around Paris agglomeration during the March field campaign of the CO2-MEGAPARIS project. The mesoscale atmospheric model Meso-NH, running at 2 km horizontal resolution, is coupled with the Town Energy Balance (TEB) urban canopy scheme and with the Interactions between Soil, Biosphere and Atmosphere CO2-reactive (ISBA-A-gs) surface scheme, allowing a full interaction of CO2 modelling between the surface and the atmosphere. Statistical scores show a good representation of the urban heat island (UHI) with stronger urban-rural contrasts on temperature at night than during the day by up to 7 °C. Boundary layer heights (BLH) have been evaluated on urban, suburban and rural sites during the campaign, and also on a suburban site over 1 yr. The diurnal cycles of the BLH are well captured, especially the onset time of the BLH increase and its growth rate in the morning, which are essential for tall tower CO2 observatories. The main discrepancy is a small negative bias over urban and suburban sites during nighttime (respectively 45 m and 5 m), leading to a few overestimations of nocturnal CO2 mixing ratios at suburban sites and a bias of +5 ppm. The diurnal CO2 cycle is generally well captured for all the sites. At the Eiffel tower, the observed spikes of CO2 maxima occur every morning exactly at the time at which the atmospheric boundary layer (ABL) growth reaches the measurement height. At suburban ground stations, CO2 measurements exhibit maxima at the beginning and at the end of each night, when the ABL is fully contracted, with a strong spatio-temporal variability. A sensitivity test without urban parameterisation removes the UHI and underpredicts nighttime BLH over urban and suburban sites, leading to large overestimation of nocturnal CO2 mixing ratio at the suburban sites (bias of +17 ppm). The agreement between observation and prediction for BLH and CO2 concentrations and urban-rural increments, both day and night, demonstrates the potential of using the urban mesoscale system in the context of inverse modelling

Dust in the wind: challenges for urban aerodynamics

NASA Astrophysics Data System (ADS)

Boris, Jay P.

2007-04-01

The fluid dynamics of airflow through a city controls the transport and dispersion of airborne contaminants. This is urban aerodynamics, not meteorology. The average flow, large-scale fluctuations and turbulence are closely coupled to the building geometry. Buildings create large "rooster-tail" wakes; there are systematic fountain flows up the backs of tall buildings; and dust in the wind can move perpendicular to or even against the locally prevailing wind. Requirements for better prediction accuracy demand time-dependent, three-dimensional CFD computations that include solar heating and buoyancy, complete landscape and building geometry specification including foliage and, realistic wind fluctuations. This fundamental prediction capability is necessary to assess urban visibility and line-of-sight sensor performance in street canyons and rugged terrain. Computing urban aerodynamics accurately is clearly a time-dependent High Performance Computing (HPC) problem. In an emergency, on the other hand, prediction technology to assess crisis information, sensor performance, and obscured line-of-sight propagation in the face of industrial spills, transportation accidents, or terrorist attacks has very tight time requirements that suggest simple approximations which tend to produce inaccurate results. In the past we have had to choose one or the other: a fast, inaccurate model or a slow accurate model. Using new fluid-dynamic principles, an urban-oriented emergency assessment system called CT-Analyst® was invented that solves this dilemma. It produces HPC-quality results for airborne contaminant scenarios nearly instantly and has unique new capabilities suited to sensor optimization. This presentation treats the design and use of CT-Analyst and discusses the developments needed for widespread use with advanced sensor and communication systems.

High Resolution Spatial Analysis of Habitat Preference of Aedes Albopictus (Diptera: Culicidae) in an Urban Environment.

PubMed

Cianci, Daniela; Hartemink, Nienke; Zeimes, Caroline B; Vanwambeke, Sophie O; Ienco, Annamaria; Caputo, Beniamino

2015-05-01

Over the past decades, the Asian tiger mosquito (Aedes albopictus (Skuse, 1895)) has emerged in many countries, and it has colonized new environments, including urban areas. The species is a nuisance and a potential vector of several human pathogens, and a better understanding of the habitat preferences of the species is needed for help in successful prevention and control. So far, the habitat preference in urban environments has not been studied in Southern European cities. In this paper, spatial statistical models were used to evaluate the relationship between egg abundances and land cover types on the campus of Sapienza University in Rome, which is taken as an example of a European urban habitat. Predictor variables included land cover types, classified in detail on a high resolution image, as well as solar radiation and month of capture. The models account for repeated measures in the same trap and are adjusted for meteorological circumstances. Vegetation and solar radiation were found to be positively related to the number of eggs. More specifically, trees were positively related to the number of eggs and the relationship with grass was negative. These findings are consistent with the species' known preference for shaded areas. The unexpected positive relationship with solar radiation is amply discussed in the paper. This study represents a first step toward a better understanding of the spatial distribution of Ae. albopictus in urban environments. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Toward an operational tool to simulate green roof hydrological impact at the basin scale: a new version of the distributed rainfall-runoff model Multi-Hydro.

PubMed

Versini, Pierre-Antoine; Gires, Auguste; Tchinguirinskaia, Ioulia; Schertzer, Daniel

2016-10-01

Currently widespread in new urban projects, green roofs have shown a positive impact on urban runoff at the building scale: decrease and slow-down of the peak discharge, and decrease of runoff volume. The present work aims to study their possible impact at the catchment scale, more compatible with stormwater management issues. For this purpose, a specific module dedicated to simulating the hydrological behaviour of a green roof has been developed in the distributed rainfall-runoff model (Multi-Hydro). It has been applied on a French urban catchment where most of the building roofs are flat and assumed to accept the implementation of a green roof. Catchment responses to several rainfall events covering a wide range of meteorological situations have been simulated. The simulation results show green roofs can significantly reduce runoff volume and the magnitude of peak discharge (up to 80%) depending on the rainfall event and initial saturation of the substrate. Additional tests have been made to assess the susceptibility of this response regarding both spatial distributions of green roofs and precipitation. It appears that the total area of greened roofs is more important than their locations. On the other hand, peak discharge reduction seems to be clearly dependent on spatial distribution of precipitation.

Estimating the urban bias of surface shelter temperatures using upper-air and satellite data. Part 2: Estimation of the urban bias

NASA Technical Reports Server (NTRS)

Epperson, David L.; Davis, Jerry M.; Bloomfield, Peter; Karl, Thomas R.; Mcnab, Alan L.; Gallo, Kevin P.

1995-01-01

A methodology is presented for estimating the urban bias of surface shelter temperatures due to the effect of the urban heat island. Multiple regression techniques were used to predict surface shelter temperatures based on the time period 1986-89 using upper-air data from the European Centre for Medium-Range Weather Forecasts (ECMWF) to represent the background climate, site-specific data to represent the local landscape, and satellite-derived data -- the normalized difference vegetation index (NDVI) and the Defense Meteorological Satellite Program (DMSP) nighttime brightness data -- to represent the urban and rural landscape. Local NDVI and DMSP values were calculated for each station using the mean NDVI and DMSP values from a 3 km x 3 km area centered over the given station. Regional NDVI and DMSP values were calculated to represent a typical rural value for each station using the mean NDVI and DMSP values from a 1 deg x 1 deg latitude-longitude area in which the given station was located. Models for the United States were then developed for monthly maximum, mean, and minimum temperatures using data from over 1000 stations in the U.S. Cooperative (COOP) Network and for monthly mean temperatures with data from over 1150 stations in the Global Historical Climate Network (GHCN). Local biases, or the differences between the model predictions using the observed NDVI and DMSP values, and the predictions using the background regional values were calculated and compared with the results of other research. The local or urban bias of U.S. temperatures, as derived from all U.S. stations (urban and rural) used in the models, averaged near 0.40 C for monthly minimum temperatures, near 0.25 C for monthly mean temperatures, and near 0.10 C for monthly maximum temperatures. The biases of monthly minimum temperatures for individual stations ranged from near -1.1 C for rural stations to 2.4 C for stations from the largest urban areas. The results of this study indicate minimal problems for global application once global NDVI and DMSP data become available.

An Investigation of the Influence of Urban Areas on Rainfall Using the TRMM Satellite and a Cloud-Mesoscale Model

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; OCStarr, David (Technical Monitor)

2002-01-01

A recent paper by Shepherd and Pierce (in press at Journal of Applied Meteorology) used rainfall data from the Precipitation Radar on NASA's Tropical Rainfall Measuring Mission's (TRMM) satellite to identify warm season rainfall anomalies downwind of major urban areas. Data (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas. Results reveal an average increase of approx. 28% in monthly rainfall rates within 30-60 kilometers downwind of the metropolis with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage changes are relative to an upwind control area. It was also found that maximum rainfall rates in the downwind impact area exceeded the mean value in the upwind control area by 48%-116%. The maximum value was generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. Results are consistent with METROMEX studies of St. Louis almost two decades ago and with more recent studies near Atlanta. A convective-mesoscale model with extensive land-surface processes is currently being employed to (a) determine if an urban heat island (UHI) thermal perturbation can induce a dynamic response to affect rainfall processes and (b) quantify the impact of the following three factors on the evolution of rainfall: (1) urban surface roughness, (2) magnitude of the UHI temperature anomaly, and (3) physical size of the UHI temperature anomaly. The sensitivity experiments are achieved by inserting a slab of land with urban properties (e.g. roughness length, albedo, thermal character) within a rural surface environment and varying the appropriate lower boundary condition parameters. The study will discuss the feasibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. The talk also introduces very preliminary results from the modeling component of the study. Such research has implications for weather forecasting, urban planning, water resource management, and understanding human impact on the environment and climate.

Temperature, ozone, and mortality in urban and non-urban counties in the northeastern United States.

PubMed

Madrigano, Jaime; Jack, Darby; Anderson, G Brooke; Bell, Michelle L; Kinney, Patrick L

2015-01-07

Most health effects studies of ozone and temperature have been performed in urban areas, due to the available monitoring data. We used observed and interpolated data to examine temperature, ozone, and mortality in 91 urban and non-urban counties. Ozone measurements were extracted from the Environmental Protection Agency's Air Quality System. Meteorological data were supplied by the National Center for Atmospheric Research. Observed data were spatially interpolated to county centroids. Daily internal-cause mortality counts were obtained from the National Center for Health Statistics (1988-1999). A two-stage Bayesian hierarchical model was used to estimate each county's increase in mortality risk from temperature and ozone. We examined county-level associations according to population density and compared urban (≥1,000 persons/mile(2)) to non-urban (<1,000 persons/mile(2)) counties. Finally, we examined county-level characteristics that could explain variation in associations by county. A 10 ppb increase in ozone was associated with a 0.45% increase in mortality (95% PI: 0.08, 0.83) in urban counties, while this same increase in ozone was associated with a 0.73% increase (95% PI: 0.19, 1.26) in non-urban counties. An increase in temperature from 70°F to 90°F (21.2°C 32.2°C) was associated with a 8.88% increase in mortality (95% PI: 7.38, 10.41) in urban counties and a 8.08% increase (95% PI: 6.16, 10.05) in non-urban counties. County characteristics, such as population density, percentage of families living in poverty, and percentage of elderly residents, partially explained the variation in county-level associations. While most prior studies of ozone and temperature have been performed in urban areas, the impacts in non-urban areas are significant, and, for ozone, potentially greater. The health risks of increasing temperature and air pollution brought on by climate change are not limited to urban areas.

Characterization of runoff from various urban catchments at different spatial scales in Beijing, China.

PubMed

Zhang, W; Che, W; Liu, D K; Gan, Y P; Lv, F F

2012-01-01

In order to investigate the characterization of runoff in storm sewer from various urban catchments, three monitoring systems at different spatial scales have been installed separately. They have been held since July 2010 in urban area of Beijing (China). The monitoring data revealed that chemical oxygen demand (COD), total suspended solids (TSS), total nitrogen (TN), total phosphorus (TP), and NH(3)-N values significantly exceed the Class V surface water quality standard developed by Ministry of Environmental Protection of the People's Republic of China (MEP). A surface solids buildup and wash off model for small watershed was adopted to analyze and discuss the process of a runoff pollutant discharge. More than a half of pollutant parameters presented a good fit to the model. However, a slightly worse-fit to the wash off model appeared in less than half of the data. Due to the influence of sewer sediments, sewer system characteristics, catchment characteristics, and other reasons, first flush was seldom observed in storm sewer runoff from these three survey areas. Meanwhile, the correlation between TSS and any other pollutant was analyzed according to cumulative load of pollutants in runoff events. An event mean concentrations (EMCs) approach was adopted to quantify the pollution of runoff. EMCs of various pollutants in storm sewer runoff between different rainfall events were slightly higher than the typical values observed in similar areas at home and abroad, according to other studies reported in literature. Based on quantitative analysis, it can be concluded that urban non-point source pollution is recognized as the major causes of quality deterioration in the receiving water bodies. This is after the point source pollution has been controlled substantially in Beijing. An integrated strategy, which combines centralized and decentralized control, along with the conditions of meteorology, hydrology, urban planning, existing drainage system, etc., will be an effective and economic approach to urban runoff pollution control.

Continuous measurements of stable isotopes of carbon dioxide and water vapour in an urban atmosphere: isotopic variations associated with meteorological conditions.

PubMed

Wada, Ryuichi; Matsumi, Yutaka; Nakayama, Tomoki; Hiyama, Tetsuya; Fujiyoshi, Yasushi; Kurita, Naoyuki; Muramoto, Kenichiro; Takanashi, Satoru; Kodama, Naomi; Takahashi, Yoshiyuki

2017-12-01

Isotope ratios of carbon dioxide and water vapour in the near-surface air were continuously measured for one month in an urban area of the city of Nagoya in central Japan in September 2010 using laser spectroscopic techniques. During the passages of a typhoon and a stationary front in the observation period, remarkable changes in the isotope ratios of CO 2 and water vapour were observed. The isotope ratios of both CO 2 and water vapour decreased during the typhoon passage. The decreases can be attributed to the air coming from an industrial area and the rainout effects of the typhoon, respectively. During the passage of the stationary front, δ 13 C-CO 2 and δ 18 O-CO 2 increased, while δ 2 H-H 2 Ov and δ 18 O-H 2 Ov decreased. These changes can be attributed to the air coming from rural areas and the air surrounding the observational site changing from a subtropical air mass to a subpolar air mass during the passage of the stationary front. A clear relationship was observed between the isotopic CO 2 and water vapour and the meteorological phenomena. Therefore, isotopic information of CO 2 and H 2 Ov could be used as a tracer of meteorological information.

Modeling of the anthropogenic heat flux and its effect on air quality over the Yangtze River Delta region, China

NASA Astrophysics Data System (ADS)

Xie, M.; Liao, J.; Wang, T.; Zhu, K.; Zhuang, B.; Han, Y.; Li, M.; Li, S.

2015-11-01

Anthropogenic heat (AH) emissions from human activities caused by urbanization can affect the city environment. Based on the energy consumption and the gridded demographic data, the spatial distribution of AH emission over the Yangtze River Delta (YRD) region is estimated. Meanwhile, a new method for the AH parameterization is developed in the WRF/Chem model, which incorporates the gridded AH emission data with the seasonal and the diurnal variations into the simulations. By running this upgraded WRF/Chem for two typical months in 2010, the impacts of AH on the meteorology and air quality over the YRD region are studied. The results show that the AH fluxes over YRD have been growing in recent decades. In 2010, the annual mean values of AH over Shanghai, Jiangsu and Zhejiang are 14.46, 2.61 and 1.63 W m-2 respectively, with the high values of 113.5 W m-2 occurring in the urban areas of Shanghai. These AH emissions can significantly change the urban heat island and urban-breeze circulations in the cities of the YRD region. In Shanghai, 2 m air temperature increases by 1.6 °C in January and 1.4 °C in July, the planetary boundary layer height rises up by 140 m in January and 160 m in July, and 10 m wind speed is enhanced by 0.7 m s-1 in January and 0.5 m s-1 in July, with higher increment at night. And the enhanced vertical movement can transport more moisture to higher levels, which causes the decrease of water vapor at the ground level and the increase in the upper PBL, and thereby induces the accumulative precipitation to increase by 15-30 % over the megacities in July. The adding AH can impact the spatial and vertical distributions of the simulated pollutants as well. The concentrations of primary air pollutants decrease near surface and increase at the upper levels, due mainly to the increases of PBLH, surface wind speed and upward air vertical movement. But surface O3 concentrations increase in the urban areas, with maximum changes of 2.5 ppb in January and 4 ppb in July. Chemical direct (the rising up of air temperature directly accelerate surface O3 formation) and indirect (the decrease in NOx at the ground results in the increase of surface O3) effects can play a significant role in O3 changes over this region. The meteorology and air pollution predictions in and around large urban areas are highly sensitive to the anthropogenic heat inputs, suggesting that AH should be considered in any climate and air quality assessment.

Numerical simulation of the effects of urban land-use changes on the local climate of multiple desert cities

NASA Astrophysics Data System (ADS)

Kamal, S. M.; Huang, H. P.; Myint, S. W.

2016-12-01

This study quantifies the effect of urbanization on local climate by numerical simulations for multiple desert cities with a wide range of urban size, baseline climatology, and composition of land cover. The numerical experiments use the Weather Research and Forecasting (WRF) model with multiple layers of nesting centered at a desert city. To extract the influence of land-use changes, twin runs are performed with each pair driven by the same time-varying lateral boundary conditions from reanalysis but different land surface conditions from Landsat observations for 1985 and 2010. The differences in the meteorological fields between the two runs are interpreted as the effects of land-use changes due to urbanization from 1985-2010. Using this strategy, simulations are carried out for five desert cities: (1) Las Vegas, United States, (2) Hotan, China, (3) Kharga, Egypt, (4) Beer Sheva, Israel, and (5) Jodhpur, India. The results of the simulations reveal a common pattern of the climatic effect of desert urbanization with nighttime warming but daytime cooling over areas where urbanization occurred. This effect is mainly confined to the urban area and is not sensitive to the size of the city or the detail of land cover in the surrounding non-urban areas. The pattern is similar in winter and summer. Exceptions to this pattern are found in a few cases in which the noisiness of local circulation, specifically monsoon and land-sea breeze, overwhelms the climatic signal induced by land-use changes. Although the local climatic responses to urbanization are qualitatively similar for the five desert cities, quantitative differences exist in the magnitudes of nighttime warming and daytime cooling. The possible reasons for those secondary differences are discussed.

Diurnal cycle of air pollution in the Kathmandu Valley, Nepal: 2. Modeling results

NASA Astrophysics Data System (ADS)

Panday, Arnico K.; Prinn, Ronald G.; SchäR, Christoph

2009-11-01

After completing a 9-month field experiment studying air pollution and meteorology in the Kathmandu Valley, Nepal, we set up the mesoscale meteorological model MM5 to simulate the Kathmandu Valley's meteorology with a horizontal resolution of up to 1 km. After testing the model against available data, we used it to address specific questions to understand the factors that control the observed diurnal cycle of air pollution in this urban basin in the Himalayas. We studied the dynamics of the basin's nocturnal cold air pool, its dissipation in the morning, and the subsequent growth and decay of the mixed layer over the valley. During mornings, we found behavior common to large basins, with upslope flows and basin-center subsidence removing the nocturnal cold air pool. During afternoons the circulation in the Kathmandu Valley exhibited patterns common to plateaus, with cooler denser air originating over lower regions west of Kathmandu arriving through mountain passes and spreading across the basin floor, thereby reducing the mixed layer depth. We also examined the pathways of pollutant ventilation out of the valley. The bulk of the pollution ventilation takes place during the afternoon, when strong westerly winds blow in through the western passes of the valley, and the pollutants are rapidly carried out through passes on the east and south sides of the valley. In the evening, pollutants first accumulate near the surface, but then are lifted slightly when katabatic flows converge underneath. The elevated polluted layers are mixed back down in the morning, contributing to the morning pollution peak. Later in the morning a fraction of the valley's pollutants travels up the slopes of the valley rim mountains before the westerly winds begin.

Downscaling a Global Climate Model to Simulate Climate Change Impacts on U.S. Regional and Urban Air Quality

NASA Technical Reports Server (NTRS)

Trail, M.; Tsimpidi, A. P.; Liu, P.; Tsigaridis, K.; Hu, Y.; Nenes, A.; Russell, A. G.

2013-01-01

Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with WRF to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the continental United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF RCM to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12km by 12km resolution, as well as the effect of evolving climate conditions on the air quality at major U.S. cities. The high resolution simulations produce somewhat different results than the coarse resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the U.S. during fall (Western U.S., Texas, Northeastern, and Southeastern U.S), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (Northeast). We also find that daily peak temperatures tend to increase in most major cities in the U.S. which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.

Separation of land-use change induced signals from noise by means of evaluating perturbed RCM ensembles: Assessing the potential impacts of urbanization and deforestation in Central Vietnam

NASA Astrophysics Data System (ADS)

Laux, Patrick; Nguyen, Phuong N. B.; Cullmann, Johannes; Kunstmann, Harald

2016-04-01

Regional climate models (RCMs) comprise both terrestrial and atmospheric compartments and thereby allowing to study land atmosphere feedbacks, and in particular the land-use and climate change impacts. In this study, a methodological framework is developed to separate the land use change induced signals in RCM simulations from noise caused by perturbed initial boundary conditions. The framework is applied for two different case studies in SE Asia, i.e. an urbanization and a deforestation scenario, which are implemented into the Weather Research and Forecasting (WRF) model. The urbanization scenario is produced for Da Nang, one of the fastest growing cities in Central Vietnam, by converting the land-use in a 20 km, 14 km, and 9 km radius around the Da Nang meteorological station systematically from cropland to urban. Likewise, three deforestation scenarios are derived for Nong Son (Central Vietnam). Based on WRF ensemble simulations with perturbed initial conditions for 2010, the signal to-noise ratio (SNR) is calculated to identify areas with pronounced signals induced by LULCC. While clear and significant signals are found for air temperature, latent and sensible heat flux in the urbanization scenario (SNR values up to 24), the signals are not pronounced for deforestation (SNR values < 1). Albeit statistically significant signals are found for precipitation, low SNR values hinder scientifically sound inferences for climate change adaptation options. It is demonstrated that ensemble simulations with more than at least 5 ensemble members are required to derive robust LULCC adaptation strategies, particularly if precipitation is considered. This is rarely done in practice, thus potentially leading to erroneous estimates of the LULCC induced signals of water and energy fluxes, which are propagated through the regional climate - hydrological model modeling chains, and finally leading to unfavorable decision support.

Urban enhancement of the heat waves in Madrid and its metropolitan area

NASA Astrophysics Data System (ADS)

Fernandez, F.; Rasilla, D.

2009-04-01

The urban heat island (UHI) is a worldwide phenomenon that causes an increase of the temperatures in the centre of the cities. The process of urbanization has developed an intense urban heat island in Madrid, with temperature differences up to 10°C higher than the surrounding rural environment. Such differences may potentially increase the magnitude and duration of heat waves within cities, exacerbating their most negative effects over human health, particularly by night, as it deprives urban residents of the cool relief found in rural areas. In this contribution we study the long term trends on warm extreme temperature episodes in the Madrid metropolitan area, and their impact at local scale, on the onw city of Madrid. For the first task, we have compared maximum and minimum temperatures from rural (Barajas and Torrejón) and urban (El Retiro, Cuatro Vientos, Getafe) stations from 1961-2008; for the second one a local network of automated meteorological stations inside the city provided hourly data from the 2002-2004 years. Finally, the 2003 heat wave is used as an example of the spatial and temporal patterns of temperature and ozone concentrations during those extreme episodes. Our results show a regional increase in the frequency and duration of those extreme warm episodes since the end of the 80´s, although their absolute magnitude remains unchanged. The urban environment exacerbates the heat load due to the persistence of the high temperatures during the night-time hours, as it is shown by the above average number of tropical nights (> 20°C) inside the urban spaces, simultaneous to the increasing trend of maximum temperatures. Besides, the diversity of urban morphologies introduces a spatial variability on the strength of this nocturnal heat load, aggravating it in the densely urbanized areas and mitigating it in the vicinities of the green areas. The regional meteorological conditions associated to these warm episodes, characterized also by low wind speed and high values of sunshine and solar irradiation, are very favourable to increases of the levels of ozone, thus exacerbating the negative effects of the heat waves.

A low cost Mobile Network System for monitoring climate and air quality of urban areas at high resolution: a preliminary application in Florence (IT) metropolitan area

NASA Astrophysics Data System (ADS)

Dibari, Camilla; Moriondo, Marco; Matese, Alessandro; Sabatini, Francesco; Trombi, Giacomo; Zaldei, Alessandro; Bindi, Marco

2013-04-01

The combination of the "Heat island effect" coupled with higher frequencies of extreme events (e.g. heat waves) due to climate change is of great concern for human health in urban areas. Anomalies of summer 2003, mentioned as possible typical climate for the near future summers (Schär et al., 2004), caused about 7,000 deaths in Italy and over 35,000 in the whole Europe. Furthermore, more than 50% of world's population is living in urban areas and, given the unprecedented urbanization rate that is expected in the next future, cities will likely be exposed to a growing environmental pressure in the following decades. Accordingly, climate monitoring of urban areas is gradually becoming a key element of planning that cannot be disregarded for an efficient public health management and for the development of a city scale Heat Waves Warning System tool, which is based on meteorological forecast of both air temperatures and humidity at a synoptic scale (Pascal et al., 2006). Building on these premises, a low cost Mobile Weather Station (MWS), to be placed on urban public transport, has been assembled. This mobile station logs every minute both meteorological variables (i.e. temperature and air humidity) and air quality parameters (i.e. atmospheric CO2 concentration and noise detection); the geographical position of each MWS's measurement is also recorded thanks to the built-in GPS antenna. The system, equipped with a data logger for data storage based on the open-source hardware platform Arduino, can also transmit data in real time via GPRS. The quality of meteorological and environmental data acquired by MWS was evaluated both on pre-existing steady meteorological stations of the metropolitan area of Florence (Petralli et al., 2010), and on professional research-grade data logger (Campbell CR800), logging air temperature in a non-aspirated shield by means of sensors at fast (thermocouple) and slower (digital) time response. Two prototypes of stations were thus designed specifically for buses or tramways and four MWSs were then installed on Florence public transport means (tramways and buses); the system is designed either to log further pollution parameters (i.e. fine particles) and to be extended to other Florence mobile vectors in order to get high resolution maps (in space and time) of meteo/environmental variables in the urban area. Coupling spatial distribution of the extreme events with information regarding those areas frequented by individuals more sensitive to climate extremes (e.g. elder people and children), prompt countermeasures (e.g. pre-warning of the nearest sanitary structures) could be timely taken. References: Pascal M, Laaidi K, Ledrans M, Baffert E, Caserio-Schönemann C, Le Tertre A, Manach J, Medina S, Rudant J, Empereur-Bissonnet P (2006) France's heat health watch warning system. Int.J.Biometeorol 50:144-153. Petralli M, Massetti L, Orlandini S (2010) Five years of thermal intra-urban monitoring in Florence (Italy) and application of climatological indices. Theor.Appl.Climatol 104:349-356. Schär C, Vidale PL, Lüthi, D, Frei C, Häberli C, Liniger MA, Appenzeller C (2004) The role of increasing temperature variability in European summer heatwaves. Nature 427:332-336.

Long-term hydrometeorological trends in the Midwest region based on a century long gridded hydrometeorological dataset and simulations from a macro-scale hydrology model

NASA Astrophysics Data System (ADS)

Chiu, C. M.; Hamlet, A. F.

2014-12-01

Climate change is likely to impact the Great Lakes region and Midwest region via changes in Great Lakes water levels, agricultural impacts, river flooding, urban stormwater impacts, drought, water temperature, and impacts to terrestrial and aquatic ecosystems. Self-consistent and temporally homogeneous long-term data sets of precipitation and temperature over the entire Great Lakes region and Midwest regions are needed to provide inputs to hydrologic models, assess historical trends in hydroclimatic variables, and downscale global and regional-scale climate models. To support these needs a new hybrid gridded meteorological forcing dataset at 1/16 degree resolution based on data from co-op station records, the U. S Historical Climatology Network (HCN) , the Historical Canadian Climate Database (HCCD), and Precipitation Regression on Independent Slopes Method (PRISM) has been assembled over the Great Lakes and Midwest region from 1915-2012 at daily time step. These data were then used as inputs to the macro-scale Variable Infiltration Capacity (VIC) hydrology model, implemented over the Midwest and Great Lakes region at 1/16 degree resolution, to produce simulated hydrologic variables that are amenable to long-term trend analysis. Trends in precipitation and temperature from the new meteorological driving data sets, as well as simulated hydrometeorological variables such as snowpack, soil moisture, runoff, and evaporation over the 20th century are presented and discussed.

Modeling green infrastructure land use changes on future air ...

EPA Pesticide Factsheets

Green infrastructure can be a cost-effective approach for reducing stormwater runoff and improving water quality as a result, but it could also bring co-benefits for air quality: less impervious surfaces and more vegetation can decrease the urban heat island effect, and also result in more removal of air pollutants via dry deposition with increased vegetative surfaces. Cooler surface temperatures can also decrease ozone formation through the increases of NOx titration; however, cooler surface temperatures also lower the height of the boundary layer resulting in more concentrated pollutants within the same volume of air, especially for primary emitted pollutants (e.g. NOx, CO, primary particulate matter). To better understand how green infrastructure impacts air quality, the interactions between all of these processes must be considered collectively. In this study, we use a comprehensive coupled meteorology-air quality model (WRF-CMAQ) to simulate the influence of planned land use changes that include green infrastructure in Kansas City (KC) on regional meteorology and air quality. Current and future land use data was provided by the Mid-America Regional Council for 2012 and 2040 (projected land use due to population growth, city planning and green infrastructure implementation). These land use datasets were incorporated into the WRF-CMAQ modeling system allowing the modeling system to propagate the changes in vegetation and impervious surface coverage on meteoro

Modelling urban rainfall-runoff responses using an experimental, two-tiered physical modelling environment

NASA Astrophysics Data System (ADS)

Green, Daniel; Pattison, Ian; Yu, Dapeng

2016-04-01

Surface water (pluvial) flooding occurs when rainwater from intense precipitation events is unable to infiltrate into the subsurface or drain via natural or artificial drainage channels. Surface water flooding poses a serious hazard to urban areas across the world, with the UK's perceived risk appearing to have increased in recent years due to surface water flood events seeming more severe and frequent. Surface water flood risk currently accounts for 1/3 of all UK flood risk, with approximately two million people living in urban areas at risk of a 1 in 200-year flood event. Research often focuses upon using numerical modelling techniques to understand the extent, depth and severity of actual or hypothetical flood scenarios. Although much research has been conducted using numerical modelling, field data available for model calibration and validation is limited due to the complexities associated with data collection in surface water flood conditions. Ultimately, the data which numerical models are based upon is often erroneous and inconclusive. Physical models offer a novel, alternative and innovative environment to collect data within, creating a controlled, closed system where independent variables can be altered independently to investigate cause and effect relationships. A physical modelling environment provides a suitable platform to investigate rainfall-runoff processes occurring within an urban catchment. Despite this, physical modelling approaches are seldom used in surface water flooding research. Scaled laboratory experiments using a 9m2, two-tiered 1:100 physical model consisting of: (i) a low-cost rainfall simulator component able to simulate consistent, uniformly distributed (>75% CUC) rainfall events of varying intensity, and; (ii) a fully interchangeable, modular plot surface have been conducted to investigate and quantify the influence of a number of terrestrial and meteorological factors on overland flow and rainfall-runoff patterns within a modelled urban setting. Terrestrial factors investigated include altering the physical model's catchment slope (0°- 20°), as well as simulating a number of spatially-varied impermeability and building density/configuration scenarios. Additionally, the influence of different storm dynamics and intensities were investigated. Preliminary results demonstrate that rainfall-runoff responses in the physical modelling environment are highly sensitive to slight increases in catchment gradient and rainfall intensity and that more densely distributed building layouts significantly increase peak flows recorded at the physical model outflow when compared to sparsely distributed building layouts under comparable simulated rainfall conditions.

Future Projection of Storm Surge at Tokyo Bay under RCP 8.5 Scenario by Meteorological-Ocean-Tide Coupled Model

NASA Astrophysics Data System (ADS)

Iwamoto, T.; Nakamura, R.; Takagawa, T.; Shibayama, T.

2016-12-01

It is clearly valuable to accomplish well-reproduced storm surge model and conduct future projection for disaster prevention. In this study, the reproducibility of Meteorological-Ocean-Tide coupled model was validated by simulating typhoon Roke (2011) storm surge, which was recorded as the highest anomaly (119cm) at Tokyo tide station (JMA) in Tokyo Bay over the last 10 years. Furthermore, the future projection (2050) under global warming scenario (RCP8.5) was conducted. The coupled model was composed of 3 models; ARW-WRFV3 (Skamarock et al., 2008), FVCOM (Chen et al., 2011) and WXTide32. WRF firstly calculated downscaled meteorological field by using FiNal anaLysis (FNL) as initial/boundary (I/B) condition. In this calculation, single layer urban canopy model (Kusaka et al., 2001) and topography data from SRTM3 (90m mesh) and GSI (50m mesh) were applied. Then the output was used as I/B condition to FVCOM, which calculated storm surge. Finally tide level was calculated by adding storm surge to astronomical tide calculated by WXTide32. For 2050 case, sea surface temperature (SST) from 26 GCM under RCP8.5 was used for constructing pseudo global warming meteorological fields. In details, ensemble average of SST variation between 2006-2015 and 2041-2060 was added to FNL's SST by following Oya et al (2016). In this case, calculating astronomical tide is omitted due to the limitation of WXTide32. The reproduced result of typhoon Roke shows that the difference of maximum tide level (first peak) to the observation is less than 10cm, the difference of second peak is about 50cm. The future projection result shows that the increase of storm surge at Tokyo tide station is about 20cm and that at Funabashi is about 30cm. This intensification is mainly caused by wind speed increment, since the variation of low pressure due to higher SST is relatively small. Moreover, Funabashi is located in front of the open space at inner part of Tokyo Bay, Tokyo tide station is similar however is installed at Tokyo harbor which has intricate terrain. This implies that the geographical condition will affect storm surge significantly for typhoon Roke-like case.

Resilience of urban ambulance services under future climate, meteorology and air pollution scenarios

NASA Astrophysics Data System (ADS)

Pope, Francis; Chapman, Lee; Fisher, Paul; Mahmood, Marliyyah; Sangkharat, Kamolrat; Thomas, Neil; Thornes, John

2017-04-01

Ambulances are an integral part of a country's infrastructure ensuring its citizens and visitors are kept healthy. The impact of weather, climate and climate change on ambulance services around the world has received increasing attention in recent years but most studies have been area specific and there is a need to establish basic relationships between ambulance data (both response and illness data) and meteorological parameters. In this presentation, the effects of temperature, other meteorological and air pollution variables on ambulance call out rates for different medical categories will be investigated. We use ambulance call out obtained from various ambulance services worldwide which have significantly different meteorologies, climatologies and pollution conditions. A time-series analysis is utilized to understand the relation between meteorological conditions, air pollutants and different call out categories. We will present findings that support the opinion that ambulance attendance call outs records are an effective and well-timed source of data and can be used for health early warning systems. Furthermore the presented results can much improve our understanding of the relationships between meteorology, climate, air pollution and human health thereby allowing for better prediction of ambulance use through the application of long and short-term weather, climate and pollution forecasts.

The Effects of a Blizzard on Urban Air Pollution.

ERIC Educational Resources Information Center

da Silva, Armando; Bein, Frederick L.

1981-01-01

The chronology and effects of a 1978 blizzard on Indianapolis' air pollution levels (ozone, sulfur dioxide, carbon monoxide) are used as a case study for geography classes. Photographs, graphs, and maps are provided as examples of meteorological data collection and interpretation. (AM)

Traffic-related particulate air pollution exposure in urban areas

NASA Astrophysics Data System (ADS)

Borrego, C.; Tchepel, O.; Costa, A. M.; Martins, H.; Ferreira, J.; Miranda, A. I.

In the last years, there has been an increase of scientific studies confirming that long- and short-term exposure to particulate matter (PM) pollution leads to adverse health effects. The development of a methodology for the determination of accumulated human exposure in urban areas is the main objective of the current work, combining information on concentrations at different microenvironments and population time-activity pattern data. A link between a mesoscale meteorological and dispersion model and a local scale air quality model was developed to define the boundary conditions for the local scale application. The time-activity pattern of the population was derived from statistical information for different sub-population groups and linked to digital city maps. Finally, the hourly PM 10 concentrations for indoor and outdoor microenvironments were estimated for the Lisbon city centre, which was chosen as the case-study, based on the local scale air quality model application for a selected period. This methodology is a first approach to estimate population exposure, calculated as the total daily values above the thresholds recommended for long- and short-term health effects. Obtained results reveal that in Lisbon city centre a large number of persons are exposed to PM levels exceeding the legislated limit value.

Environmental Consequences of Rapid Urbanization in Zhejiang Province, East China

PubMed Central

Yang, Xuchao; Yue, Wenze; Xu, Honghui; Wu, Jingsheng; He, Yue

2014-01-01

Since reforms carried out in the late 1970s, China has experienced unprecedented rates of urban growth. Remote sensing data and surface observational data are used to investigate the urbanization process and related environmental consequences, focusing on extreme heat events and air pollution, in Zhejiang Province (ZJP, East China). Examination of satellite-measured nighttime light data indicates rapid urbanization in ZJP during the past decade, initially forming three urban clusters. With rapid urban sprawl, a significant Urban Heat Island (UHI) effect has emerged. During extreme heat events in summer, the UHI effect significantly exacerbates nocturnal heat stress in highly urbanized areas. Taking a long-term view, urbanization also causes additional hot days and hot degree days in urban areas. Urbanization also imposes a heavy burden on local and regional air quality in ZJP. Degraded visibility and an increase in haze days are observed at most meteorological stations, especially in the three urban clusters. The results show that urbanization has led to serious environmental problems in ZJP, not only on the city scale, but also on the regional scale. Maintaining a balance between the continuing process of urbanization and environmental sustainability is a major issue facing the local government. PMID:25019266

Environmental consequences of rapid urbanization in zhejiang province, East china.

PubMed

Yang, Xuchao; Yue, Wenze; Xu, Honghui; Wu, Jingsheng; He, Yue

2014-07-11

Since reforms carried out in the late 1970s, China has experienced unprecedented rates of urban growth. Remote sensing data and surface observational data are used to investigate the urbanization process and related environmental consequences, focusing on extreme heat events and air pollution, in Zhejiang Province (ZJP, East China). Examination of satellite-measured nighttime light data indicates rapid urbanization in ZJP during the past decade, initially forming three urban clusters. With rapid urban sprawl, a significant Urban Heat Island (UHI) effect has emerged. During extreme heat events in summer, the UHI effect significantly exacerbates nocturnal heat stress in highly urbanized areas. Taking a long-term view, urbanization also causes additional hot days and hot degree days in urban areas. Urbanization also imposes a heavy burden on local and regional air quality in ZJP. Degraded visibility and an increase in haze days are observed at most meteorological stations, especially in the three urban clusters. The results show that urbanization has led to serious environmental problems in ZJP, not only on the city scale, but also on the regional scale. Maintaining a balance between the continuing process of urbanization and environmental sustainability is a major issue facing the local government.

[Climate and ecologic state of urban areas in Eastern Kazakhstan].

PubMed

Onaev, S T; Grebeneva, O V; Shadetova, A Zh; Kurmangalieva, D S; Balaeva, E A

2011-01-01

Ust-Kamenogorsk territory was demonstrated to have climate peculiarities depending on local relief and unfavorable wind conditions of ventilation, that could promote formation of highly chemically loaded zones. Suggested evaluation methods provide qualitative and quantitative assessment of climate parameters for individual areas of residence. Marking areas according to residence comfort for population, based on analysis of geographic position of the studied territory, in accordance with repetition of meteorologic processes, could specify major factors influencing climate on urban territories of modem Kazakhstan cities.

EVALUATING THE USE OF OUTPUTS FROM COMPREHENSIVE METEOROLOGICAL MODELS IN AIR QUALITY MODELING APPLICATIONS

EPA Science Inventory

Currently used dispersion models, such as the AMS/EPA Regulatory Model (AERMOD), process routinely available meteorological observations to construct model inputs. Thus, model estimates of concentrations depend on the availability and quality of Meteorological observations, as we...

Ozone pollution in China: A review of concentrations, meteorological influences, chemical precursors, and effects.

PubMed

Wang, Tao; Xue, Likun; Brimblecombe, Peter; Lam, Yun Fat; Li, Li; Zhang, Li

2017-01-01

High concentrations of ozone in urban and industrial regions worldwide have long been a major air quality issue. With the rapid increase in fossil fuel consumption in China over the past three decades, the emission of chemical precursors to ozone-nitrogen oxides and volatile organic compounds-has increased sharply, surpassing that of North America and Europe and raising concerns about worsening ozone pollution in China. Historically, research and control have prioritized acid rain, particulate matter, and more recently fine particulate matter (PM 2.5 ). In contrast, less is known about ozone pollution, partly due to a lack of monitoring of atmospheric ozone and its precursors until recently. This review summarizes the main findings from published papers on the characteristics and sources and processes of ozone and ozone precursors in the boundary layer of urban and rural areas of China, including concentration levels, seasonal variation, meteorology conducive to photochemistry and pollution transport, key production and loss processes, ozone dependence on nitrogen oxides and volatile organic compounds, and the effects of ozone on crops and human health. Ozone concentrations exceeding the ambient air quality standard by 100-200% have been observed in China's major urban centers such as Jing-Jin-Ji, the Yangtze River delta, and the Pearl River delta, and limited studies suggest harmful effect of ozone on human health and agricultural corps; key chemical precursors and meteorological conditions conductive to ozone pollution have been investigated, and inter-city/region transport of ozone is significant. Several recommendations are given for future research and policy development on ground-level ozone. Copyright © 2016 Elsevier B.V. All rights reserved.

Numerical modeling of flows and pollutant dispersion within and above urban street canyons under unstable thermal stratification by large-eddy simulation

NASA Astrophysics Data System (ADS)

Chan, Ming-Chung; Liu, Chun-Ho

2013-04-01

Recently, with the ever increasing urban areas in developing countries, the problem of air pollution due to vehicular exhaust arouses the concern of different groups of people. Understanding how different factors, such as urban morphology, meteorological conditions and human activities, affect the characteristics of street canyon ventilation, pollutant dispersion above urban areas and pollutant re-entrainment from the shear layer can help us improve air pollution control strategies. Among the factors mentioned above, thermal stratification is a significant one determining the pollutant transport behaviors in certain situation, e.g. when the urban surface is heated by strong solar radiation, which, however, is still not widely explored. The objective of this study is to gain an in-depth understanding of the effects of unstable thermal stratification on the flows and pollutant dispersion within and above urban street canyons through numerical modeling using large-eddy simulation (LES). In this study, LES equipped with one-equation subgrid-scale (SGS) model is employed to model the flows and pollutant dispersion within and above two-dimensional (2D) urban street canyons (flanked by idealized buildings, which are square solid bars in these models) under different intensities of unstable thermal stratifications. Three building-height-to-street-width (aspect) ratios, 0.5, 1 and 2, are included in this study as a representation of different building densities. The prevailing wind flow above the urban canopy is driven by background pressure gradient, which is perpendicular to the street axis, while the condition of unstable thermal stratification is induced by applying a higher uniform temperature on the no-slip urban surface. The relative importance between stratification and background wind is characterized by the Richardson number, with zero value as a neutral case and negative value as an unstable case. The buoyancy force is modeled by Boussinesq approximation and the intensity of stratification is controlled by the gravitational acceleration. The urban characteristic is modeled by periodic boundary conditions at the domain inlet-outlet and spanwise extent, so as to simulate the infinitely long and wide urban area. Pollutant dispersion is modeled by scalar transport with the pollutant area source on the ground of the first street canyon and by open boundary condition at the domain outlet. The numerical models are solved with incremental time steps until it reaches the pseudo steady-state. Afterwards, a set of data is collected for each model such that the temporal averages of mean and fluctuating field variables do not vary significantly if more time steps are included. It is found that the ventilation performance is improved and the plume dispersion in shear layer is enhanced when the stratification is more unstable. The mean flows, turbulent transports of pollutant and momentum, pollutant concentration fields in different unstable stratifications will be discussed with profile and contour plots. The ventilation performance of a street canyon evaluated by air exchange rate (ACH) and pollutant exchange rate (PCH) at roof level and the plume dispersion characterized by the mean plume height and dispersion coefficient in shear layer will also be discussed.

Identifying pollution sources and predicting urban air quality using ensemble learning methods

NASA Astrophysics Data System (ADS)

Singh, Kunwar P.; Gupta, Shikha; Rai, Premanjali

2013-12-01

In this study, principal components analysis (PCA) was performed to identify air pollution sources and tree based ensemble learning models were constructed to predict the urban air quality of Lucknow (India) using the air quality and meteorological databases pertaining to a period of five years. PCA identified vehicular emissions and fuel combustion as major air pollution sources. The air quality indices revealed the air quality unhealthy during the summer and winter. Ensemble models were constructed to discriminate between the seasonal air qualities, factors responsible for discrimination, and to predict the air quality indices. Accordingly, single decision tree (SDT), decision tree forest (DTF), and decision treeboost (DTB) were constructed and their generalization and predictive performance was evaluated in terms of several statistical parameters and compared with conventional machine learning benchmark, support vector machines (SVM). The DT and SVM models discriminated the seasonal air quality rendering misclassification rate (MR) of 8.32% (SDT); 4.12% (DTF); 5.62% (DTB), and 6.18% (SVM), respectively in complete data. The AQI and CAQI regression models yielded a correlation between measured and predicted values and root mean squared error of 0.901, 6.67 and 0.825, 9.45 (SDT); 0.951, 4.85 and 0.922, 6.56 (DTF); 0.959, 4.38 and 0.929, 6.30 (DTB); 0.890, 7.00 and 0.836, 9.16 (SVR) in complete data. The DTF and DTB models outperformed the SVM both in classification and regression which could be attributed to the incorporation of the bagging and boosting algorithms in these models. The proposed ensemble models successfully predicted the urban ambient air quality and can be used as effective tools for its management.

Atmospheric Model Evaluation Tool for meteorological and air quality simulations

EPA Pesticide Factsheets

The Atmospheric Model Evaluation Tool compares model predictions to observed data from various meteorological and air quality observation networks to help evaluate meteorological and air quality simulations.

Use of a handheld low-cost sensor to explore the effect of urban design features on local-scale spatial and temporal air quality variability.

PubMed

Miskell, Georgia; Salmond, Jennifer A; Williams, David E

2018-04-01

Portable low-cost instruments have been validated and used to measure ambient nitrogen dioxide (NO 2 ) at multiple sites over a small urban area with 20min time resolution. We use these results combined with land use regression (LUR) and rank correlation methods to explore the effects of traffic, urban design features, and local meteorology and atmosphere chemistry on small-scale spatio-temporal variations. We measured NO 2 at 45 sites around the downtown area of Vancouver, BC, in spring 2016, and constructed four different models: i) a model based on averaging concentrations observed at each site over the whole measurement period, and separate temporal models for ii) morning, iii) midday, and iv) afternoon. Redesign of the temporal models using the average model predictors as constants gave three 'hybrid' models that used both spatial and temporal variables. These accounted for approximately 50% of the total variation with mean absolute error±5ppb. Ranking sites by concentration and by change in concentration across the day showed a shift of high NO 2 concentrations across the central city from morning to afternoon. Locations could be identified in which NO 2 concentration was determined by the geography of the site, and others as ones in which the concentration changed markedly from morning to afternoon indicating the importance of temporal controls. Rank correlation results complemented LUR in identifying significant urban design variables that impacted NO 2 concentration. High variability across a relatively small space was partially described by predictor variables related to traffic (bus stop density, speed limits, traffic counts, distance to traffic lights), atmospheric chemistry (ozone, dew point), and environment (land use, trees). A high-density network recording continuously would be needed fully to capture local variations. Copyright © 2017 Elsevier B.V. All rights reserved.

Greater Baltimore Open Air: an Internet of Things (IoT) approach to citizen science and community-driven climate, air quality, and urban heat island monitoring

NASA Astrophysics Data System (ADS)

Scott, A.; Kelley, C.; Azdoud, Y.; Ambikapathi, R.; Hobson, M.; Lehman, A.; Ghugare, P.; He, C.; Zaitchik, B. F.; Waugh, D.; McCormack, M.; Baja, K.

2017-12-01

Anthropogenic activities alter the urban surface and surface atmosphere, generating heat and pollutants that have known detrimental impacts on health. Monitoring these environmental variables in urban environments is made difficult by the spatial heterogeneity of urban environments, meaning that two nearby locations may have significantly different temperatures, humidities, or gas concentrations. Thus, urban monitoring often requires more densely placed monitors than current standards or budgets allow. Recent advances in low-cost sensors and Internet of Things (IoT) enabled hardware offer possible solutions. We present an autonomous wireless, open-source, IoT-enabled environmental monitor called a WeatherCube, developed for the Greater Baltimore Open Air project, funded in part by the EPA SmartCity Challenge. The WeatherCube is suitable for urban monitoring and capable of measuring meteorological variables (temperature and humidity) as well as air quality (ozone, nitrogen dioxide, and sulfur dioxide). The WeatherCube devices were built in collaboration with Johns Hopkins University, local government, and community members, including through an innovative job training program. Monitors are hosted by community partners and libraries throughout Baltimore city and surrounding communities. We present the first wave of data collected by the Greater Baltimore Open Air project and compare it to data collected by the Maryland Department of the Environment (MDE). Additionally, we will provide an overview of our experience engaging with the local makers, citizen scientists, and environmental groups to improve their urban environmental monitoring. By developing low-cost devices tailored for urban environmental monitoring, we present an innovative model for both conducting research and community outreach.

Effects of the Urban Heat Island on Aerosol pH

NASA Astrophysics Data System (ADS)

Battaglia, M., Jr.; Douglas, S.; Hennigan, C. J.

2017-12-01

The urban heat island (UHI) is a widely observed phenomenon whereby urban environments have higher temperature (T) and lower relative humidity (RH) than surrounding suburban and rural areas. Both of these factors affect the partitioning of semi-volatile species found in the atmosphere, such as nitric acid and ammonia. These species are inherently tied to aerosol pH, which is a key parameter driving some atmospheric chemical processes and environmental effects of aerosols. In this study, we characterized the effect of the UHI on aerosol pH in Baltimore, MD and Chicago, IL. These cities were selected based on differences in climatology, source influences, and atmospheric composition. Meteorological and atmospheric composition data from the urban centers and surrounding rural locations were used as inputs to the ISORROPIA-II aerosol thermodynamic model to compute gas/particle partitioning, aerosol liquid water content, and aerosol pH. Dramatic differences in aerosol liquid water (ALW) content were found in both cities and were attributable to the T and RH differences (UHI effect). The urban-rural differences in ALW result in urban aerosol pH that is systematically lower (more acidic) than rural aerosol pH for identical atmospheric composition. The UHI in Baltimore is most intense during the summer and at night, with differences of up to 1 pH unit predicted during these times. Similarly, the UHI in Chicago is most intense during the summer and at night; however, the atmospheric composition in Chicago shows a mediating effect, with differences of up to 0.65 pH units predicted during these times. These results are likely to have broad implications for chemistry occurring in and around urban atmospheres globally, although the magnitude of the effect may differ based on the UHI characteristic of each urban environment.

Crowdsourcing urban air temperatures from smartphone battery temperatures

NASA Astrophysics Data System (ADS)

Overeem, Aart; Robinson, James C. R.; Leijnse, Hidde; Steeneveld, Gert-Jan; Horn, Berthold K. P.; Uijlenhoet, Remko

2014-05-01

Accurate air temperature observations in urban areas are important for meteorology and energy demand planning. They are indispensable to study the urban heat island effect and the adverse effects of high temperatures on human health. However, the availability of temperature observations in cities is often limited. Here we show that relatively accurate air temperature information for the urban canopy layer can be obtained from an alternative, nowadays omnipresent source: smartphones. In this study, battery temperatures were collected by an Android application for smartphones. It has been shown that a straightforward heat transfer model can be employed to estimate daily mean air temperatures from smartphone battery temperatures for eight major cities around the world. The results demonstrate the enormous potential of this crowdsourcing application for real-time temperature monitoring in densely populated areas. Battery temperature data were collected by users of an Android application for cell phones (opensignal.com). The application automatically sends battery temperature data to a server for storage. In this study, battery temperatures are averaged in space and time to obtain daily averaged battery temperatures for each city separately. A regression model, which can be related to a physical model, is employed to retrieve daily air temperatures from battery temperatures. The model is calibrated with observed air temperatures from a meteorological station of an airport located in or near the city. Time series of air temperatures are obtained for each city for a period of several months, where 50% of the data is for independent verification. The methodology has been applied to Buenos Aires, London, Los Angeles, Paris, Mexico City, Moscow, Rome, and Sao Paulo. The evolution of the retrieved air temperatures often correspond well with the observed ones. The mean absolute error of daily air temperatures is less than 2 degrees Celsius, and the bias is within 1 degree Celsius. This shows that monitoring air temperatures employing an Android application holds great promise. This study will particularly focus on new results: The methodology has been applied to data from three cities in the Netherlands (Amsterdam, Rotterdam, and Utrecht) for the period June - August 2013. It is shown that on average 282 battery temperature readings per day are already sufficient to accurately estimate daily-averaged air temperatures. Results clearly deteriorate when on average only 80 battery temperature readings are available. Since 75% of the world's population has a cell phone, 20% of the land surface of the earth has cellular telephone coverage, and 500 million devices use the Android operating system, there is a huge potential for measuring air temperatures employing cell phones. This could eventually lead to real-time world-wide temperature maps over the continents.

APPLICATION OF THE URBANIZED VERSION OF MM5 FOR HOUSTON

EPA Science Inventory

Since most of the primary atmospheric pollutants are emitted inside the roughness sub-layer (RSL) and consequently the first chemical reactions and dispersion occur in this layer, it is necessary to generate detailed meteorological fields inside the RSL to perform air quality m...

On the competition among aerosol number, size and composition in predicting CCN variability: a multi-annual field study in an urbanized desert.

PubMed

Crosbie, E; Youn, J-S; Balch, B; Wonaschütz, A; Shingler, T; Wang, Z; Conant, W C; Betterton, E A; Sorooshian, A

2015-02-10

A 2-year data set of measured CCN (cloud condensation nuclei) concentrations at 0.2 % supersaturation is combined with aerosol size distribution and aerosol composition data to probe the effects of aerosol number concentrations, size distribution and composition on CCN patterns. Data were collected over a period of 2 years (2012-2014) in central Tucson, Arizona: a significant urban area surrounded by a sparsely populated desert. Average CCN concentrations are typically lowest in spring (233 cm -3 ), highest in winter (430 cm -3 ) and have a secondary peak during the North American monsoon season (July to September; 372 cm -3 ). There is significant variability outside of seasonal patterns, with extreme concentrations (1 and 99 % levels) ranging from 56 to 1945 cm -3 as measured during the winter, the season with highest variability. Modeled CCN concentrations based on fixed chemical composition achieve better closure in winter, with size and number alone able to predict 82% of the variance in CCN concentration. Changes in aerosol chemical composition are typically aligned with changes in size and aerosol number, such that hygroscopicity can be parameterized even though it is still variable. In summer, models based on fixed chemical composition explain at best only 41% (pre-monsoon) and 36% (monsoon) of the variance. This is attributed to the effects of secondary organic aerosol (SOA) production, the competition between new particle formation and condensational growth, the complex interaction of meteorology, regional and local emissions and multi-phase chemistry during the North American monsoon. Chemical composition is found to be an important factor for improving predictability in spring and on longer timescales in winter. Parameterized models typically exhibit improved predictive skill when there are strong relationships between CCN concentrations and the prevailing meteorology and dominant aerosol physicochemical processes, suggesting that similar findings could be possible in other locations with comparable climates and geography.

Thermal conditions in selected urban and semi-natural habitats, important for the forensic entomology.

PubMed

Michalski, Marek; Nadolski, Jerzy

2018-06-01

A long-term study on thermal conditions in selected urban and semi-natural habitats, where human corpses are likely to be found, was conducted in the city of Lodz (Central Poland). Thermal data were collected during two years at nine sites and compared with corresponding data from the nearest permanent meteorological station at Lodz Airport (ICAO code: EPLL). The conditions closest to those at the meteorological station prevailed in the deciduous forest, coefficient of determination R 2 for those sets of data was above 0.96. The open field was characterized by high daily amplitudes, especially during spring, while the site in the allotment gardens was characterized by relatively high winter temperatures. The conditions prevailing in all closed space sites were very diverse and only slightly similar to the external ones. The most distinct site was an unheated basement in a tenement house, where temperature was almost always above 0°C and daily amplitudes were negligible. Copyright © 2018 Elsevier B.V. All rights reserved.

Meteorological Processes Affecting Air Quality – Research and Model Development Needs

EPA Science Inventory

Meteorology modeling is an important component of air quality modeling systems that defines the physical and dynamical environment for atmospheric chemistry. The meteorology models used for air quality applications are based on numerical weather prediction models that were devel...

The CASA Dallas Fort Worth Remote Sensing Network ICT for Urban Disaster Mitigation

NASA Astrophysics Data System (ADS)

Chandrasekar, Venkatachalam; Chen, Haonan; Philips, Brenda; Seo, Dong-jun; Junyent, Francesc; Bajaj, Apoorva; Zink, Mike; Mcenery, John; Sukheswalla, Zubin; Cannon, Amy; Lyons, Eric; Westbrook, David

2013-04-01

The dual-polarization X-band radar network developed by the U.S. National Science Foundation Engineering Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) has shown great advantages for observing and prediction of hazardous weather events in the lower atmosphere (1-3 km above ground level). The network is operating though a scanning methodology called DCAS, distributed collaborative adaptive sensing, which is designed to focus on particular interesting regions of the atmosphere and disseminate information for decision-making to multiple end-users, such as emergency managers and policy analysts. Since spring 2012, CASA and the North Central Texas Council of Governments (NCTCOG) have embarked the development of Dallas Fort Worth (DFW) urban remote sensing network, including 8-node of dual-polarization X-band radars, in the populous DFW Metroplex (pop. 6.3 million in 2010). The main goal of CASA DFW urban demonstration network is to protect the safety and prosperity of humans and ecosystems through research activities that include: 1) to demonstrate the DCAS operation paradigm developed by CASA; 2) to create high-resolution, three-dimensional mapping of the meteorological conditions; 3) to help the local emergency managers issue impacts-based warnings and forecasts for severe wind, tornado, hail, and flash flood hazards. The products of this radar network will include single and multi-radar data, vector wind retrieval, quantitative precipitation estimation and nowcasting, and numerical weather predictions. In addition, the high spatial and temporal resolution rainfall products from CASA can serve as a reliable data input for distributed hydrological models in urban area. This paper presents the information and communication link between radars, rainfall product generation, hydrologic model link and end user community in the Dallas Fort Worth Urban Network. Specific details of the Information and Communication Technologies (ICT) between the various subsystems are presented.

Using a gradient boosting model to improve the performance of low-cost aerosol monitors in a dense, heterogeneous urban environment

NASA Astrophysics Data System (ADS)

Johnson, Nicholas E.; Bonczak, Bartosz; Kontokosta, Constantine E.

2018-07-01

The increased availability and improved quality of new sensing technologies have catalyzed a growing body of research to evaluate and leverage these tools in order to quantify and describe urban environments. Air quality, in particular, has received greater attention because of the well-established links to serious respiratory illnesses and the unprecedented levels of air pollution in developed and developing countries and cities around the world. Though numerous laboratory and field evaluation studies have begun to explore the use and potential of low-cost air quality monitoring devices, the performance and stability of these tools has not been adequately evaluated in complex urban environments, and further research is needed. In this study, we present the design of a low-cost air quality monitoring platform based on the Shinyei PPD42 aerosol monitor and examine the suitability of the sensor for deployment in a dense heterogeneous urban environment. We assess the sensor's performance during a field calibration campaign from February 7th to March 25th 2017 with a reference instrument in New York City, and present a novel calibration approach using a machine learning method that incorporates publicly available meteorological data in order to improve overall sensor performance. We find that while the PPD42 performs well in relation to the reference instrument using linear regression (R2 = 0.36-0.51), a gradient boosting regression tree model can significantly improve device calibration (R2 = 0.68-0.76). We discuss the sensor's performance and reliability when deployed in a dense, heterogeneous urban environment during a period of significant variation in weather conditions, and important considerations when using machine learning techniques to improve the performance of low-cost air quality monitors.

Meteorologically-adjusted trend analysis of surface observed ozone at three monitoring sites in Delhi, India: 2007-2011

NASA Astrophysics Data System (ADS)

Biswas, J.; Farooqui, Z.; Guttikunda, S. K.

2012-12-01

It is well known that meteorological parameters have significant impact on surface ozone concentrations. Therefore it is important to remove the effects of meteorology on ozone concentrations to correctly estimate long-term trends in ozone levels due to the alterations in precursor emissions. This is important for the development of effectual control strategies. In this study surface observed ozone trends in New Delhi are analyzed using Komogorov-Zurbenko (KZ) filter, US EPA ozone adjustment due to weather approach and the classification and regression tree method. The statistical models are applied to the ozone data at three observational sites in New Delhi metropolitan areas, 1) Income Tax Office (ITO) 2) Sirifort and 3) Delhi College of Engineering (DCE). The ITO site is located adjacent to a traffic crossing, Sirifort is an urban site and the DCE site is located in a residential area. The ITO site is also influenced by local industrial emissions. DCE has higher ozone levels than the other two sites. It was found that ITO has lowest ozone concentrations amongst the three sites due to ozone titrating due to industrial and on-road mobile NOx emissions. The statistical methods employed can assess ozone trends at these sites with a high degree of confidence and the results can be used to gauge the effectiveness of control strategies on surface ozone levels in New Delhi.

Analysis of the potential of near-ground measurements of CO2 and CH4 in London, UK, for the monitoring of city-scale emissions using an atmospheric transport model

NASA Astrophysics Data System (ADS)

Boon, Alex; Broquet, Grégoire; Clifford, Deborah J.; Chevallier, Frédéric; Butterfield, David M.; Pison, Isabelle; Ramonet, Michel; Paris, Jean-Daniel; Ciais, Philippe

2016-06-01

Carbon dioxide (CO2) and methane (CH4) mole fractions were measured at four near-ground sites located in and around London during the summer of 2012 with a view to investigating the potential of assimilating such measurements in an atmospheric inversion system for the monitoring of the CO2 and CH4 emissions in the London area. These data were analysed and compared with simulations using a modelling framework suited to building an inversion system: a 2 km horizontal resolution south of England configuration of the transport model CHIMERE driven by European Centre for Medium-Range Weather Forecasts (ECMWF) meteorological forcing, coupled to a 1 km horizontal resolution emission inventory (the UK National Atmospheric Emission Inventory). First comparisons reveal that local sources, which cannot be represented in the model at a 2 km resolution, have a large impact on measurements. We evaluate methods to filter out the impact of some of the other critical sources of discrepancies between the measurements and the model simulation except that of the errors in the emission inventory, which we attempt to isolate. Such a separation of the impact of errors in the emission inventory should make it easier to identify the corrections that should be applied to the inventory. Analysis is supported by observations from meteorological sites around the city and a 3-week period of atmospheric mixing layer height estimations from lidar measurements. The difficulties of modelling the mixing layer depth and thus CO2 and CH4 concentrations during the night, morning and late afternoon lead to focusing on the afternoon period for all further analyses. The discrepancies between observations and model simulations are high for both CO2 and CH4 (i.e. their root mean square (RMS) is between 8 and 12 parts per million (ppm) for CO2 and between 30 and 55 parts per billion (ppb) for CH4 at a given site). By analysing the gradients between the urban sites and a suburban or rural reference site, we are able to decrease the impact of uncertainties in the fluxes and transport outside the London area and in the model domain boundary conditions. We are thus able to better focus attention on the signature of London urban CO2 and CH4 emissions in the atmospheric CO2 and CH4 concentrations. This considerably improves the statistical agreement between the model and observations for CO2 (with model-data RMS discrepancies that are between 3 and 7 ppm) and to a lesser degree for CH4 (with model-data RMS discrepancies that are between 29 and 38 ppb). Between one of the urban sites and either the rural or suburban reference site, selecting the gradients during periods wherein the reference site is upwind of the urban site further decreases the statistics of the discrepancies in general, though not systematically. In a further attempt to focus on the signature of the city anthropogenic emission in the mole fraction measurements, we use a theoretical ratio of gradients of carbon monoxide (CO) to gradients of CO2 from fossil fuel emissions in the London area to diagnose observation-based fossil fuel CO2 gradients, and compare them with the fossil fuel CO2 gradients simulated with CHIMERE. This estimate increases the consistency between the model and the measurements when considering only one of the two urban sites, even though the two sites are relatively close to each other within the city. While this study evaluates and highlights the merit of different approaches for increasing the consistency between the mesoscale model and the near-ground data, and while it manages to decrease the random component of the analysed model-data discrepancies to an extent that should not be prohibitive to extracting the signal from the London urban emissions, large biases, the sign of which depends on the measurement sites, remain in the final model-data discrepancies. Such biases are likely related to local emissions to which the urban near-ground sites are highly sensitive. This questions our current ability to exploit urban near-ground data for the atmospheric inversion of city emissions based on models at spatial resolution coarser than 2 km. Several measurement and modelling concepts are discussed to overcome this challenge.

CityFlux perfluorocarbon tracer experiments

NASA Astrophysics Data System (ADS)

Petersson, F. K.; Martin, D.; White, I. R.; Henshaw, S. J.; Nickless, G.; Longley, I.; Percival, C. J.; Gallagher, M.; Shallcross, D. E.

2010-01-01

In June 2006, two perfluorocarbon tracer experiments were conducted in central Manchester UK as part of the CityFlux campaign. The main aim was to investigate vertical dispersion in an urban area during convective conditions, but dispersion mechanisms within the street network were also studied. Paired receptors were used in most cases where one receptor was located at ground level and one at roof level. One receptor was located on the roof of Portland Tower which is an 80 m high building in central Manchester. Source receptor distances in the two experiments varied between 120 and 600 m. The results reveal that maximum concentration was sometimes found at roof level rather than at ground level implying the effectiveness of convective forces on dispersion. The degree of vertical dispersion was found to be dependent on source receptor distance as well as on building height in proximity to the release site. Evidence of flow channelling in a street canyon was also found. Both a Gaussian profile and a street network model were applied and the results show that the urban topography may lead to highly effective flow channelling which therefore may be a very important dispersion mechanism should the right meteorological conditions prevail. The experimental results from this campaign have also been compared with a simple urban dispersion model that was developed during the DAPPLE framework and show good agreement with this. The results presented here are some of the first published regarding vertical dispersion. More tracer experiments are needed in order to further characterise vertical concentration profiles and their dependence on, for instance, atmospheric stability. The impact of urban topography on pollutant dispersion is important to focus on in future tracer experiments in order to improve performance of models as well as for our understanding of the relationship between air quality and public health.

CityFlux perfluorocarbon tracer experiments

NASA Astrophysics Data System (ADS)

Petersson, F. K.; Martin, D.; White, I. R.; Henshaw, S. J.; Nickless, G.; Longley, I.; Percival, C. J.; Gallagher, M.; Shallcross, D. E.

2010-07-01

In June 2006, two perfluorocarbon tracer experiments were conducted in central Manchester UK as part of the CityFlux campaign. The main aim was to investigate vertical dispersion in an urban area during convective conditions, but dispersion mechanisms within the street network were also studied. Paired receptors were used in most cases where one receptor was located at ground level and one at roof level. One receptor was located on the roof of Portland Tower which is an 80 m high building in central Manchester. Source receptor distances in the two experiments varied between 120 and 600 m. The results reveal that maximum concentration was sometimes found at roof level rather than at ground level implying the effectiveness of convective forces on dispersion. The degree of vertical dispersion was found to be dependent on source receptor distance as well as on building height in proximity to the release site. Evidence of flow channelling in a street canyon was also found. Both a Gaussian profile and a street network model were applied and the results show that the urban topography may lead to highly effective flow channelling which therefore may be a very important dispersion mechanism should the right meteorological conditions prevail. The experimental results from this campaign have also been compared with a simple urban dispersion model that was developed during the DAPPLE framework and show good agreement with this. The results presented here are some of the first published regarding vertical dispersion. More tracer experiments are needed in order to further characterise vertical concentration profiles and their dependence on, for instance, atmospheric stability. The impact of urban topography on pollutant dispersion is important to focus on in future tracer experiments in order to improve performance of models as well as for our understanding of the relationship between air quality and public health.

A multifaceted approach to understanding dynamic urban processes: satellites, surveys, and censuses.

NASA Astrophysics Data System (ADS)

Jones, B.; Balk, D.; Montgomery, M.; Liu, Z.

2014-12-01

Urbanization will arguably be the most significant demographic trend of the 21st century, particularly in fast-growing regions of the developing world. Characterizing urbanization in a spatial context, however, is a difficult task given only the moderate resolution data provided by traditional sources of demographic data (i.e., censuses and surveys). Using a sample of five world "mega-cities" we demonstrate how new satellite data products and new analysis of existing satellite data, when combined with new applications of census and survey microdata, can reveal more about cities and urbanization in combination than either data type can by itself. In addition to the partially modelled Global Urban-Rural Mapping Project (GRUMP) urban extents we consider four sources of remotely sensed data that can be used to estimate urban extents; the NOAA Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) intercallibrated nighttime lights time series data, the newer NOAA Visible Infrared Imager Radiometer Suite (VIIRS) nighttime lights data, the German Aerospace Center (DLR) radar satellite data, and Dense Sampling Method (DSM) analysis of the NASA scatterometer data. Demographic data come from national censuses and/or georeferenced survey data from the Demographic & Health Survey (DHS) program. We overlay demographic and remotely sensed data (e.g., Figs 1, 2) to address two questions; (1) how well do satellite derived measures of urban intensity correlate with demographic measures, and (2) how well are temporal changes in the data correlated. Using spatial regression techniques, we then estimate statistical relationships (controlling for influences such as elevation, coastal proximity, and economic development) between the remotely sensed and demographic data and test the ability of each to predict the other. Satellite derived imagery help us to better understand the evolution of the built environment and urban form, while the underlying demographic data provide information regarding composition of urban population change. Combining these types of data yields important, high resolution spatial information that provides a more accurate understanding of urban processes.

First results from the International Urban Energy Balance Model Comparison: Model Complexity

NASA Astrophysics Data System (ADS)

Blackett, M.; Grimmond, S.; Best, M.

2009-04-01

A great variety of urban energy balance models has been developed. These vary in complexity from simple schemes that represent the city as a slab, through those which model various facets (i.e. road, walls and roof) to more complex urban forms (including street canyons with intersections) and features (such as vegetation cover and anthropogenic heat fluxes). Some schemes also incorporate detailed representations of momentum and energy fluxes distributed throughout various layers of the urban canopy layer. The models each differ in the parameters they require to describe the site and the in demands they make on computational processing power. Many of these models have been evaluated using observational datasets but to date, no controlled comparisons have been conducted. Urban surface energy balance models provide a means to predict the energy exchange processes which influence factors such as urban temperature, humidity, atmospheric stability and winds. These all need to be modelled accurately to capture features such as the urban heat island effect and to provide key information for dispersion and air quality modelling. A comparison of the various models available will assist in improving current and future models and will assist in formulating research priorities for future observational campaigns within urban areas. In this presentation we will summarise the initial results of this international urban energy balance model comparison. In particular, the relative performance of the models involved will be compared based on their degree of complexity. These results will inform us on ways in which we can improve the modelling of air quality within, and climate impacts of, global megacities. The methodology employed in conducting this comparison followed that used in PILPS (the Project for Intercomparison of Land-Surface Parameterization Schemes) which is also endorsed by the GEWEX Global Land Atmosphere System Study (GLASS) panel. In all cases, models were run offline to ensure no feedback to larger scale conditions within the modelling domain. Initially, participants were issued with just forcing data from an unknown urban site (termed "Alpha"); in subsequent stages, further details of the site were provided. Results from each stage, for each participating model, were then compared using a variety of statistical and graphical techniques. * The EGU2009-5713 Team: C.S.B. Grimmond1, M. Blackett1, M. Best2 and J. Barlow3and J.-J. Baik4, S. Belcher3, S. Bohnenstengel3, I. Calmet5, F. Chen6, A. Dandou7, K. Fortuniak8, M. Gouvea1, R. Hamdi9, M. Hendry2, H. Kondo10, S. Krayenhoff11, S. H. Lee4, T. Loridan1, A. Martilli12, S. Miao13, K. Oleson6, G. Pigeon14, A. Porson2,3, F. Salamanca12, L. Shashua-Bar15, G.-J. Steeneveld16, M. Tombrou7, J. Voogt17, N. Zhang18. 1King's College London, UK, 2UK Met Office, UK, 3University of Reading, UK, 4Seoul National University, Korea, 5Ecole Centrale de Nantes, France, 6National Center for Atmospheric Research, USA, 7University of Athens, Greece, 8University of Ł ódź , Poland, 9Royal Meteorological Institute, Belgium, 10National Institute of Advanced Industrial Science and Technology, Japan, 11University of British Columbia, Canada, 12CIEMAT, Spain, 13IUM, CMA, China, 14Meteo France, France, 15Ben Gurion University, Israel, 16Wageningen University, Netherlands, 17University of Western Ontario, Canada, 18Nanjing University, China.

Outdoor comfort study in Rio de Janeiro: site-related context effects on reported thermal sensation

NASA Astrophysics Data System (ADS)

Krüger, E.; Drach, P.; Broede, P.

2017-03-01

Aimed at climate-responsive urban design for tropical areas, the paper attempts to answer the question whether the site-related context affects in some way the perceptual assessment of the microclimate by users of outdoor spaces. Our hypothesis was that visual cues resulting from urban design are important components of the outdoor thermal perception. Monitoring was carried out alongside the administration of standard comfort questionnaires throughout summer periods in 2012-2015 in pedestrian areas of downtown Rio de Janeiro (22° 54 10 S, 43° 12 27 W), Brazil. Campaigns took place at different points, pre-defined in respect of urban geometry attributes. For the measurements, a Davis Vantage Pro2 weather station was employed to which a gray globe thermometer was attached. Two thermal indices were used for assessing the overall meteorological conditions and comfort levels in the outdoor locations: physiological equivalent temperature (PET) and universal thermal climate index (UTCI). Our results suggest that thermal sensation in Rio depends to a large extent on the thermal environment as described by air temperature, PET, or UTCI, and that urban geometry (expressed by the sky-view factor (SVF)) may modify this relationship with increased building density associated to warmer sensation votes under moderate heat stress conditions. This relationship however reverses under strong heat stress with warmer sensations in less obstructed locations, and disappears completely under still higher heat stress, where meteorological conditions, and not the site's SVF, will drive thermal sensation.

Outdoor comfort study in Rio de Janeiro: site-related context effects on reported thermal sensation.

PubMed

Krüger, E; Drach, P; Broede, P

2017-03-01

Aimed at climate-responsive urban design for tropical areas, the paper attempts to answer the question whether the site-related context affects in some way the perceptual assessment of the microclimate by users of outdoor spaces. Our hypothesis was that visual cues resulting from urban design are important components of the outdoor thermal perception. Monitoring was carried out alongside the administration of standard comfort questionnaires throughout summer periods in 2012-2015 in pedestrian areas of downtown Rio de Janeiro (22° 54 10 S, 43° 12 27 W), Brazil. Campaigns took place at different points, pre-defined in respect of urban geometry attributes. For the measurements, a Davis Vantage Pro2 weather station was employed to which a gray globe thermometer was attached. Two thermal indices were used for assessing the overall meteorological conditions and comfort levels in the outdoor locations: physiological equivalent temperature (PET) and universal thermal climate index (UTCI). Our results suggest that thermal sensation in Rio depends to a large extent on the thermal environment as described by air temperature, PET, or UTCI, and that urban geometry (expressed by the sky-view factor (SVF)) may modify this relationship with increased building density associated to warmer sensation votes under moderate heat stress conditions. This relationship however reverses under strong heat stress with warmer sensations in less obstructed locations, and disappears completely under still higher heat stress, where meteorological conditions, and not the site's SVF, will drive thermal sensation.

Assessment of urban heat Island for Craiova from satellite-based LST

NASA Astrophysics Data System (ADS)

Udristioiu, Mihaela Tinca; Velea, Liliana; Bojariu, Roxana; Sararu, Silviu Constantin

2017-12-01

The urban heat island is defined as an excess of heating in urban areas compared with surrounding rural zones which is illustrated by higher surface and air temperatures in the inner part of the cities. The aim of this study is to identify the UHI effect for Craiova - the largest city in the South-Western part of Romania - and to assess its intensity during summer. To this end, MODIS Land surface temperature (LST) for day and night for summer months (June, July, August), in the interval 2002-2017, as well as yearly Land Cover Type (LCT) data also from MODIS were employed. Furthermore, measurements of air and soil temperature from meteorological station Craiova, available from the National Meteorological Administration database, were used to investigate their relation with LST. The analysis shows that in the urban area of Craiova the long-term summer mean LST is about 4 °C (2 °C), higher than in the rural area during daytime (nighttime). During high temperatures episodes, the mean daytime LST reaches 45-47 °C in the city, while the difference from the rural surrounding area is of 2-3 °C. A high correlation (0.77-0.83) is found between LST and air temperature for all land-use types in the area considered. Both LST and 2m-air temperature time-series manifest an increasing linear tendency over the period considered, being more pronounced during the day.

METEOROLOGICAL AND TRANSPORT MODELING

EPA Science Inventory

Advanced air quality simulation models, such as CMAQ, as well as other transport and dispersion models, require accurate and detailed meteorology fields. These meteorology fields include primary 3-dimensional dynamical and thermodynamical variables (e.g., winds, temperature, mo...

Regional/Urban Air Quality Modeling Assessment over China Using the Models-3/CMAQ System

NASA Astrophysics Data System (ADS)

Fu, J. S.; Jang, C. C.; Streets, D. G.; Li, Z.; Wang, L.; Zhang, Q.; Woo, J.; Wang, B.

2004-12-01

China is the world's most populous country with a fast growing economy that surges in energy comsumption. It has become the second largest energy consumer after the United States although the per capita level is much lower than those found in developed or developing countries. Air pollution has become one of the most important problems of megacities such as Beijing and Shanghai and has serious impacts on public health, causes urban and regional haze. The Models-3/CMAQ modeling application that has been conducted to simulate multi-pollutants in China is presented. The modeling domains cover East Asia (36-kmx36-km) including Japan, South Korea, Korea DPR, Indonesia, Thailand, India and Mongolia, East China (12-kmx12-km) and Beijing/Tianjing, Shanghai (4-kmx4-km). For this study, the Asian emission inventory based on the emission estimates of the year 2000 that supported the NASA TRACE-P program is used. However, the TRACE-P emission inventory was developed for a different purpose such as global modeling. TRACE-P emission inventory may not be practical in urban area. There is no China national emission inventory available. Therefore, TRACE-P emission inventory is used on the East Asia and East China domains. The 8 districts of Beijing and Shanghai local emissions inventory are used to replace TRACE-P in 4-km domains. The meteorological data for the Models-3/CMAQ run are extracted from MM5. The model simulation is performed during the period January 1-20 and July 1-20, 2001 that presented the winter and summer time for China areas. The preliminary model results are shown O3 concentrations are in the range of 80 -120 ppb in the urban area. Lower urban O3 concentrations are shown in Beijing areas, possibly due to underestimation of urban man-made VOC emissions in the TRACE-P inventory and local inventory. High PM2.5 (70ug/m3 in summer and 150ug/m3 in winter) were simulated over metropolitan & downwind areas with significant secondary constituents. More comprehensive simulations in the Beijing, Shanghai areas are presented with sensitivity analysis. A comparison against available ozone and PM measurement data in Beijing, Shanghai is presented. The local emission inventory improvement in China is to be suggested to investigate. The modeling configuration of the Beijing 4-km x 4-km domain is to demonstrate the development of cost-effective control strategies for the air pollution control such as 2008 Olympic Game air quality management plan.

Smog episodes, fine particulate pollution and mortality in China.

PubMed

Zhou, Maigeng; He, Guojun; Fan, Maoyong; Wang, Zhaoxi; Liu, Yang; Ma, Jing; Ma, Zongwei; Liu, Jiangmei; Liu, Yunning; Wang, Linhong; Liu, Yuanli

2015-01-01

Starting from early January 2013, northern China was hit by multiple prolonged and severe smog events which were characterized by extremely high-level concentrations of ambient fine particulate matter (PM2.5) with hourly peaks of PM2.5 over 800 µg/m(3). However, the consequences of this severe air pollution are largely unknown. This study investigates the acute effect of the smog episodes and PM2.5 on mortality for both urban and rural areas in northern China. We collected PM2.5, mortality, and meteorological data for 5 urban city districts and 2 rural counties in Beijing, Tianjin and Hebei Province of China from January 1, 2013 through December 31, 2013. We employed the generalized additive models to estimate the associations between smog episodes or PM2.5 and daily mortality for each district/county. Without any meteorological control, the smog episodes are positively and statistically significantly associated with mortality in 5 out of 7 districts/counties. However, the findings are sensitive to the meteorological factors. After controlling for temperature, humidity, dew point and wind, the statistical significance disappears in all urban districts. In contrast, the smog episodes are consistently and statistically significantly associated with higher total mortality and mortality from cardiovascular/respiratory diseases in the two rural counties. In Ji County, a smog episode is associated with 6.94% (95% Confidence Interval, -0.20 to 14.58) increase in overall mortality, and in Ci County it is associated with a 19.26% (95% CI, 6.66-33.34) increase in overall mortality. The smog episodes kill people primarily through its impact on cardiovascular and respiratory diseases. On average, a smog episode is associated with 11.66% (95% CI, 3.12-20.90) increase in cardiovascular and respiratory mortality in Ji County, and it is associated with a 22.23% (95% CI, 8.11-38.20) increase in cardiovascular and respiratory mortality in Ci County. A 10 μg/m(3) increase in PM2.5 concentration is associated with 0.88% (95% CI, 0.3-1.46) increase in overall mortality and 1.2% (95% CI, 0.55-1.85) in Ji County. A 10 μg/m(3) increase in PM2.5 concentration is associated with 0.55% (95% CI, -0.02 to 1.13) increase in overall mortality in Ci County. The findings suggest that the smog episodes and fine particulate have bigger and more detrimental impacts on rural residents, especially for those living close to big and polluted cities. The smog episodes and PM2.5 are statistically associated with mortality in rural areas of China. The associations for urban areas are not statistically significant. Copyright © 2014 Elsevier Inc. All rights reserved.

Understanding how roadside concentrations of NOx are influenced by the background levels, traffic density, and meteorological conditions using Boosted Regression Trees

NASA Astrophysics Data System (ADS)

Sayegh, Arwa; Tate, James E.; Ropkins, Karl

2016-02-01

Oxides of Nitrogen (NOx) is a major component of photochemical smog and its constituents are considered principal traffic-related pollutants affecting human health. This study investigates the influence of background concentrations of NOx, traffic density, and prevailing meteorological conditions on roadside concentrations of NOx at UK urban, open motorway, and motorway tunnel sites using the statistical approach Boosted Regression Trees (BRT). BRT models have been fitted using hourly concentration, traffic, and meteorological data for each site. The models predict, rank, and visualise the relationship between model variables and roadside NOx concentrations. A strong relationship between roadside NOx and monitored local background concentrations is demonstrated. Relationships between roadside NOx and other model variables have been shown to be strongly influenced by the quality and resolution of background concentrations of NOx, i.e. if it were based on monitored data or modelled prediction. The paper proposes a direct method of using site-specific fundamental diagrams for splitting traffic data into four traffic states: free-flow, busy-flow, congested, and severely congested. Using BRT models, the density of traffic (vehicles per kilometre) was observed to have a proportional influence on the concentrations of roadside NOx, with different fitted regression line slopes for the different traffic states. When other influences are conditioned out, the relationship between roadside concentrations and ambient air temperature suggests NOx concentrations reach a minimum at around 22 °C with high concentrations at low ambient air temperatures which could be associated to restricted atmospheric dispersion and/or to changes in road traffic exhaust emission characteristics at low ambient air temperatures. This paper uses BRT models to study how different critical factors, and their relative importance, influence the variation of roadside NOx concentrations. The paper highlights the importance of either setting up local background continuous monitors or improving the quality and resolution of modelled UK background maps and the need to further investigate the influence of ambient air temperature on NOx emissions and roadside NOx concentrations.

Analysis of airborne particulate matter pollution in Timisoara city urban area and correlations between measurements and meteorological data

NASA Astrophysics Data System (ADS)

Lungu, Mihai; Lungu, Antoanetta; Stefu, Nicoleta; Neculae, Adrian; Strambeanu, Nicolae

2017-01-01

Air pollution is known to have many adverse effects, among which those on human health are considered the most important. Healthy people of all ages can be adversely affected by high levels of air pollutants. Nanoparticles can be considered among the most harmful of all pollutants as they can penetrate straight into the lungs and blood stream. Their role in the aging process has also recently been revealed. In Romania, practically in all important urban areas (Bucureşti, Iaşi, Timişoara, Braşov, Baia Mare, etc.) the daily limit values for airborne particulate matter are exceeded, so more efforts in controlling air quality are required, along with more research and policies with positive impact on reducing the pollutants concentration in air. The approaches that have been developed to assess the air quality and health impacts of pollution sources are based on analytical methods such as source apportionment, factor analyses, and the measurement of source-relevant indicator compounds. The goal of the present study is to offer preliminary but relevant information on the particulate matter distribution in the city of Timisoara, Romania. Measurements of inhalable coarse and fine particles in two areas of the city, the most affected by industrial particulate emissions, were performed in days with various meteorological conditions. Meteorological parameters for the specific measurement days were recorded (wind speed and direction, humidity, temperature, pressure, etc.) and the influence of these parameters on the particulate matter dispersion was studied. The results show that the meteorological conditions cause differences between airborne particulate matter distributions in different days in the same zones. Measurements were made in northern and southern areas of the city of Timisoara because previous results have shown high levels of airborne particulate matter in these areas.

Interactions of Chemistry and Meteorology: Transforming Air Pollution into Climate Change

NASA Astrophysics Data System (ADS)

Dickerson, R. R.

2009-05-01

PThe common goal of understanding and protecting Earth's environment has brought together chemists and meteorologists, despite the once widely held view that these are natural adversaries. Historically, dynamics, physics, chemistry, and biology were explored as isolated aspects of air quality and climate, but nature has proved to be much more interesting than that. Emissions and atmospheric photochemistry create air pollutants, but meteorology drives day to day variability in air quality. Air pollution, no matter how severe, has no substantive impact on global atmospheric composition or climate unless it is transported away from the sources, usually through frontal passage and advection, isentropic lifting or, especially lofting in deep convective clouds and thunderstorms. At higher altitudes, greater actinic flux accelerates photochemistry, stronger winds speed dispersal, and lower temperatures slow losses while amplifying radiative heating of greenhouse forcing substance such as ozone and carbonaceous aerosols. Examples include the transport of reactive nitrogen compounds from one part of North America to another, or on to the remote North Atlantic and Europe. Although measurement of NOy and NHx gases and particles still presents an analytical challenge, these trace species have major impacts on ecosystems and biogeochemical cycles. In East Asia chemistry and meteorology conspire to intensify long-range, even intercontinental transport of mineral dust and air pollutants. Recent discovery of a nonlocal dynamical driver to the Urban Heat Island effect shows that the adverse impact of urbanization can cascade to exacerbate heat stress, photochemical smog, and haze well downwind. A balanced consideration of meteorology and chemistry not only helps to identify and understand environmental problems, it can also provide powerful, policy relevant science that has led to success stories such as a regional approach to emissions controls and cleaner air over the eastern US.

Characteristics of Fine Particles in an Urban Atmosphere-Relationships with Meteorological Parameters and Trace Gases.

PubMed

Zhang, Tianhao; Zhu, Zhongmin; Gong, Wei; Xiang, Hao; Fang, Ruimin

2016-08-10

Atmospheric fine particles (diameter < 1 μm) attract a growing global health concern and have increased in urban areas that have a strong link to nucleation, traffic emissions, and industrial emissions. To reveal the characteristics of fine particles in an industrial city of a developing country, two-year measurements of particle number size distribution (15.1 nm-661 nm), meteorological parameters, and trace gases were made in the city of Wuhan located in central China from June 2012 to May 2014. The annual average particle number concentrations in the nucleation mode (15.1 nm-30 nm), Aitken mode (30 nm-100 nm), and accumulation mode (100 nm-661 nm) reached 4923 cm(-3), 12193 cm(-3) and 4801 cm(-3), respectively. Based on Pearson coefficients between particle number concentrations and meteorological parameters, precipitation and temperature both had significantly negative relationships with particle number concentrations, whereas atmospheric pressure was positively correlated with the particle number concentrations. The diurnal variation of number concentration in nucleation mode particles correlated closely with photochemical processes in all four seasons. At the same time, distinct growth of particles from nucleation mode to Aitken mode was only found in spring, summer, and autumn. The two peaks of Aitken mode and accumulation mode particles in morning and evening corresponded obviously to traffic exhaust emissions peaks. A phenomenon of "repeated, short-lived" nucleation events have been created to explain the durability of high particle concentrations, which was instigated by exogenous pollutants, during winter in a case analysis of Wuhan. Measurements of hourly trace gases and segmental meteorological factors were applied as proxies for complex chemical reactions and dense industrial activities. The results of this study offer reasonable estimations of particle impacts and provide references for emissions control strategies in industrial cities of developing countries.

IDC Re-Engineering Phase 2 Iteration E2 Use Case Realizations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harris, James M.; Burns, John F.; Hamlet, Benjamin R.

2016-06-01

This architecturally significant use case describes how the System acquires meteorological data to build atmospheric models used in automatic and interactive processing of infrasound data. The System requests the latest available high-resolution global meteorological data from external data centers and puts it into the correct formats for generation of infrasound propagation models. The system moves the meteorological data from Data Acquisition Partition to the Data Processing Partition and stores the meteorological data. The System builds a new atmospheric model based on the meteorological data. This use case is architecturally significant because it describes acquiring meteorological data from various sources andmore » creating dynamic atmospheric transmission model to support the prediction of infrasonic signal detection« less

The Impact of Urban Growth and Climate Change on Heat Stress in an Australian City

NASA Astrophysics Data System (ADS)

Chapman, S.; Mcalpine, C. A.; Thatcher, M. J.; Salazar, A.; Watson, J. R.

2017-12-01

Over half of the world's population lives in urban areas. Most people will therefore be exposed to climate change in an urban environment. One of the climate risks facing urban residents is heat stress, which can lead to illness and death. Urban residents are at increased risk of heat stress due to the urban heat island effect. The urban heat island is a modification of the urban environment and increases temperatures on average by 2°C, though the increase can be much higher, up to 8°C when wind speeds and cloud cover are low. The urban heat island is also expected to increase in the future due to urban growth and intensification, further exacerbating urban heat stress. Climate change alters the urban heat island due to changes in weather (wind speed and cloudiness) and evapotranspiration. Future urban heat stress will therefore be affected by urban growth and climate change. The aim of this study was to examine the impact of urban growth and climate change on the urban heat island and heat stress in Brisbane, Australia. We used CCAM, the conformal cubic atmospheric model developed by the CSIRO, to examine temperatures in Brisbane using scenarios of urban growth and climate change. We downscaled the urban climate using CCAM, based on bias corrected Sea Surface Temperatures from the ACCESS1.0 projection of future climate. We used Representative Concentration Pathway (RCP) 8.5 for the periods 1990 - 2000, 2049 - 2060 and 2089 - 2090 with current land use and an urban growth scenario. The present day climatology was verified using weather station data from the Australian Bureau of Meteorology. We compared the urban heat island of the present day with the urban heat island with climate change to determine if climate change altered the heat island. We also calculated heat stress using wet-bulb globe temperature and apparent temperature for the climate change and base case scenarios. We found the urban growth scenario increased present day temperatures by 0.5°C in the inner city and by 6°C during a period of hot days. The scenarios of future temperature are ongoing and will show how heat stress will change in Brisbane when both urban growth and climate change are considered.

Mapping Regional Impervious Surface Distribution from Night Time Light: The Variability across Global Cities

NASA Astrophysics Data System (ADS)

Lin, M.; Yang, Z.; Park, H.; Qian, S.; Chen, J.; Fan, P.

2017-12-01

Impervious surface area (ISA) has become an important indicator for studying urban environments, but mapping ISA at the regional or global scale is still challenging due to the complexity of impervious surface features. The Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) nighttime light data is (NTL) and Resolution Imaging Spectroradiometer (MODIS) are the major remote sensing data source for regional ISA mapping. A single regression relationship between fractional ISA and NTL or various index derived based on NTL and MODIS vegetation index (NDVI) data was established in many previous studies for regional ISA mapping. However, due to the varying geographical, climatic, and socio-economic characteristics of different cities, the same regression relationship may vary significantly across different cities in the same region in terms of both fitting performance (i.e. R2) and the rate of change (Slope). In this study, we examined the regression relationship between fractional ISA and Vegetation Adjusted Nighttime light Urban Index (VANUI) for 120 randomly selected cities around the world with a multilevel regression model. We found that indeed there is substantial variability of both the R2 (0.68±0.29) and slopes (0.64±0.40) among individual regressions, which suggests that multilevel/hierarchical models are needed for accuracy improvement of future regional ISA mapping .Further analysis also let us find the this substantial variability are affected by climate conditions, socio-economic status, and urban spatial structures. However, all these effects are nonlinear rather than linear, thus could not modeled explicitly in multilevel linear regression models.

Land-use regression panel models of NO2 concentrations in Seoul, Korea

NASA Astrophysics Data System (ADS)

Kim, Youngkook; Guldmann, Jean-Michel

2015-04-01

Transportation and land-use activities are major air pollution contributors. Since their shares of emissions vary across space and time, so do air pollution concentrations. Despite these variations, panel data have rarely been used in land-use regression (LUR) modeling of air pollution. In addition, the complex interactions between traffic flows, land uses, and meteorological variables, have not been satisfactorily investigated in LUR models. The purpose of this research is to develop and estimate nitrogen dioxide (NO2) panel models based on the LUR framework with data for Seoul, Korea, accounting for the impacts of these variables, and their interactions with spatial and temporal dummy variables. The panel data vary over several scales: daily (24 h), seasonally (4), and spatially (34 intra-urban measurement locations). To enhance model explanatory power, wind direction and distance decay effects are accounted for. The results show that vehicle-kilometers-traveled (VKT) and solar radiation have statistically strong positive and negative impacts on NO2 concentrations across the four seasonal models. In addition, there are significant interactions with the dummy variables, pointing to VKT and solar radiation effects on NO2 concentrations that vary with time and intra-urban location. The results also show that residential, commercial, and industrial land uses, and wind speed, temperature, and humidity, all impact NO2 concentrations. The R2 vary between 0.95 and 0.98.

The effects of season and meteorology on human mortality in tropical climates: a systematic review.

PubMed

Burkart, Katrin; Khan, Md Mobarak Hossain; Schneider, Alexandra; Breitner, Susanne; Langner, Marcel; Krämer, Alexander; Endlicher, Wilfried

2014-07-01

Research in the field of atmospheric science and epidemiology has long recognized the health effects of seasonal and meteorological conditions. However, little scientific knowledge exists to date about the impacts of atmospheric parameters on human mortality in tropical regions. Working within the scope of this systematic review, this investigation conducted a literature search using different databases; original research articles were chosen according to pre-defined inclusion and exclusion criteria. Both seasonal and meteorological effects were considered. The findings suggest that high amounts of rainfall and increasing temperatures cause a seasonal excess in infectious disease mortality and are therefore relevant in regions and populations in which such diseases are prevalent. On the contrary, moderately low and very high temperatures exercise an adverse effect on cardio-respiratory mortality and shape the mortality pattern in areas and sub-groups in which these diseases are dominant. Atmospheric effects were subject to population-specific factors such as age and socio-economic status and differed between urban and rural areas. The consequences of climate change as well as environmental, epidemiological and social change (e.g., emerging non-communicable diseases, ageing of the population, urbanization) suggest a growing relevance of heat-related excess mortality in tropical regions. © The Author 2014. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Understanding Biogenic and Anthropogenic Trace Gas Variations Measured Near Cool, CA in June 2010

NASA Astrophysics Data System (ADS)

Klein, B. Z.; Flowers, B. A.; Gorkowski, K.; Dubey, M. K.; Knighton, W. B.; Floerchinger, C.; Herndon, S. C.; Fast, J. D.; Zaveri, R. A.

2011-12-01

Trace gas signatures produced by forested and urban areas differ greatly. Forested areas are dominated by gases produced during photosynthesis and respiration: CO2 and volatile organic compounds (VOCs) including terpenes and isoprene. Urban areas are heavily influenced by vehicle exhaust emissions and have elevated levels of CO, NOx and aromatic hydrocarbons such as benzene. Ozone is produced as a byproduct of both of these sources; it is produced when NOx from urban areas reacts with either anthropogenic or biogenic hydrocarbons. The Carbonaceous Aerosol and Radiative Effects Study (CARES) campaign was conducted during June 2010, in part to observe the evolution of urban air masses as they mix into rural locations and to better understand anthropogenic-biogenic photochemical interactions. The campaign included two ground-based sampling sites, one in Sacramento, CA (T0) and one downwind, approximately 70km NE, rurally located near Cool, CA (T1). In situ measurements of CO2, CO, O3, NO and multiple different VOCs were performed at the T1 site during the study, and are analyzed here to gain insights into the chemistry and transport of these trace gases. Comparisons between these trace gases coupled with transport modeling is used to delineate biogenic and anthropogenic sources. Additionally, comparisons between trace gases produced predominately by biogenic sources provide valuable information on how meteorology affects their production. Two atmospheric models (HYSPLIT back-trajectories and WRF forecasts) are used to predict transport episodes, where polluted air masses from the Sacramento or more distant San Francisco areas are transported to Cool. The two models display significant overlap for eleven different transport episodes during the study period. Both models also agree on two transport-free multiple-day periods. By examining the periods during which the models are in agreement, we are able to characterize with high certainty the trace gas signatures of local biogenic sources and also the significance of short-range transported anthropogenic trace gases.

Fog in the coastal region of southern Brazil: seasonal variations

NASA Astrophysics Data System (ADS)

Krusche, N.; Gomes, C.

2009-05-01

Fog forecasting, especially advection fog, is important because a large port is located at Rio Grande, 32° S and 52° W. Fogs discontinue the cargo transport and prevent entrance of ships in the port, causing great financial loss. Atmospheric and oceanographic conditions associated to fog formation are been investigated, especially those that happen during advection fog. The result of this characterization will facilitate the forecast using mesoscale numerical models. The research started with a climatology of fog in the region, in two locations which are 2° of latitude apart, with an average temperature difference of 3°C. The observation of fog is a standard record at conventional meteorological stations. Data from this study was obtained from the Meteorological Station of Rio Grande, which belongs to the Instituto Nacional de Meteorologia network, and from the Meteorological Station operated by the Division of Meteorology of Department of Airspace Control in Porto Alegre. The period of this study is from January 1990 to December 2005. The distribution of the monthly total of fog observations shows that they occur mainly between May and August, with maximum in June. In all seasons of the year the total number of fogs is greater than in Porto Alegre in Rio Grande. There was a decrease in the average annual number of fogs from the 90s to the last five years of research, which can be attributed to urbanization around the places of observation. It increases the temperature in the layers closer to the soil and decreases the available moisture, making the occurrence of radiation fog. Atmospheric and oceanographic conditions, prevalent during these occurrences, will be examined next. The another goal is to compare the data of advection fog in Rio Grande, obtained from images of the type ARGUS in Cassino beach, with those recorded by Meteorological Station. This work is partially financed by FINEP and CAPES.

Distinct wind convergence patterns in the Mexico City basin due to the interaction of the gap winds with the synoptic flow

NASA Astrophysics Data System (ADS)

de Foy, B.; Clappier, A.; Molina, L. T.; Molina, M. J.

2006-04-01

Mexico City lies in a high altitude basin where air quality and pollutant fate is strongly influenced by local winds. The combination of high terrain with weak synoptic forcing leads to weak and variable winds with complex circulation patterns. A gap wind entering the basin in the afternoon leads to very different wind convergence lines over the city depending on the meteorological conditions. Surface and upper-air meteorological observations are analysed during the MCMA-2003 field campaign to establish the meteorological conditions and obtain an index of the strength and timing of the gap wind. A mesoscale meteorological model (MM5) is used in combination with high-resolution satellite data for the land surface parameters and soil moisture maps derived from diurnal ground temperature range. A simple method to map the lines of wind convergence both in the basin and on the regional scale is used to show the different convergence patterns according to episode types. The gap wind is found to occur on most days of the campaign and is the result of a temperature gradient across the southern basin rim which is very similar from day to day. Momentum mixing from winds aloft into the surface layer is much more variable and can determine both the strength of the flow and the pattern of the convergence zones. Northerly flows aloft lead to a weak jet with an east-west convergence line that progresses northwards in the late afternoon and early evening. Westerlies aloft lead to both stronger gap flows due to channelling and winds over the southern and western basin rim. This results in a north-south convergence line through the middle of the basin starting in the early afternoon. Improved understanding of basin meteorology will lead to better air quality forecasts for the city and better understanding of the chemical regimes in the urban atmosphere.

[Spatial epidemiological study on malaria epidemics in Hainan province].

PubMed

Wen, Liang; Shi, Run-He; Fang, Li-Qun; Xu, De-Zhong; Li, Cheng-Yi; Wang, Yong; Yuan, Zheng-Quan; Zhang, Hui

2008-06-01

To better understand the characteristics of spatial distribution of malaria epidemics in Hainan province and to explore the relationship between malaria epidemics and environmental factors, as well to develop prediction model on malaria epidemics. Data on Malaria and meteorological factors were collected in all 19 counties in Hainan province from May to Oct., 2000, and the proportion of land use types of these counties in this period were extracted from digital map of land use in Hainan province. Land surface temperatures (LST) were extracted from MODIS images and elevations of these counties were extracted from DEM of Hainan province. The coefficients of correlation of malaria incidences and these environmental factors were then calculated with SPSS 13.0, and negative binomial regression analysis were done using SAS 9.0. The incidence of malaria showed (1) positive correlations to elevation, proportion of forest land area and grassland area; (2) negative correlations to the proportion of cultivated area, urban and rural residents and to industrial enterprise area, LST; (3) no correlations to meteorological factors, proportion of water area, and unemployed land area. The prediction model of malaria which came from negative binomial regression analysis was: I (monthly, unit: 1/1,000,000) = exp (-1.672-0.399xLST). Spatial distribution of malaria epidemics was associated with some environmental factors, and prediction model of malaria epidemic could be developed with indexes which extracted from satellite remote sensing images.

Spatial and temporal variability of PM levels and composition in a complex summer atmospheric scenario in Barcelona (NE Spain)

NASA Astrophysics Data System (ADS)

Viana, M.; Pérez, C.; Querol, X.; Alastuey, A.; Nickovic, S.; Baldasano, J. M.

Summer atmospheric coastal dynamics exert a significant influence on the levels and composition of atmospheric particulate matter (PM) in the North-Eastern Iberian Peninsula. Summer atmospheric scenarios in this region present a high degree of complexity as they are characterised by the absence of synoptic-scale air mass advections, the development of breeze circulations, enhanced photochemistry, local mineral dust re-suspension and the occurrence of African dust outbreaks. Three sampling sites were selected in Barcelona (NE Spain), an urban coastal site surrounded by complex topography. Regional dust modelling (DREAM) and high resolution meteorological modelling (MM5) were used to interpret PM levels and composition at the three sites. The results outline the effect of breeze dynamics and thermal internal boundary layer formation as the main meteorological drivers of the hourly evolution of PM levels. Levels of crustal components, secondary inorganic and carbon species are higher during the night, and only the marine aerosol content is higher during the day. Nitrate levels are higher during the night due to the thermal stability on NH 4NO 3. Sulphate levels are higher during the night as a consequence of the drainage flows. Lidar measurements and model results signalled the occurrence of two African dust episodes during the study period which mainly affected the free troposphere over Barcelona.

Dispersion of Perfluorocarbon Tracers within the Salt Lake Valley during VTMX 2000

NASA Astrophysics Data System (ADS)

Fast, Jerome D.; Allwine, K. Jerry; Dietz, Russell N.; Clawson, Kirk L.; Torcolini, Joel C.

2006-06-01

Six perfluorocarbon tracer experiments were conducted in Salt Lake City, Utah, during October 2000 as part of the Vertical Transport and Mixing (VTMX) field campaign. Four tracers were released at different sites to obtain information on dispersion during stable conditions within down-valley flow, canyon outflow, and interacting circulations in the downtown area. Some of the extensive tracer data that were collected are presented in the context of the meteorological field campaign measurements. Tracer measurements at building-top sites in the downtown area and along the lower slopes of the Wasatch Front indicated that vertical mixing processes transported material up to at least 180 m above the valley floor, although model simulations suggest that tracers were transported upward to much higher elevations. Tracer data provided evidence of downward mixing of canyon outflow, upward mixing within down-valley flow, horizontal transport above the surface stable layer, and transport within horizontal eddies produced by the interaction of canyon and down-valley flows. Although point meteorological measurements are useful in evaluating the forecasts produced by mesoscale models, the tracer data provide valuable information on how the time-varying three-dimensional mean and turbulent motions over urban and valley spatial scales affect dispersion. Although the mean tracer transport predicted by the modeling system employed in this study was qualitatively similar to the measurements, improvements are needed in the treatment of turbulent vertical mixing.

A novel hybrid forecasting model for PM₁₀ and SO₂ daily concentrations.

PubMed

Wang, Ping; Liu, Yong; Qin, Zuodong; Zhang, Guisheng

2015-02-01

Air-quality forecasting in urban areas is difficult because of the uncertainties in describing both the emission and meteorological fields. The use of incomplete information in the training phase restricts practical air-quality forecasting. In this paper, we propose a hybrid artificial neural network and a hybrid support vector machine, which effectively enhance the forecasting accuracy of an artificial neural network (ANN) and support vector machine (SVM) by revising the error term of the traditional methods. The hybrid methodology can be described in two stages. First, we applied the ANN or SVM forecasting system with historical data and exogenous parameters, such as meteorological variables. Then, the forecasting target was revised by the Taylor expansion forecasting model using the residual information of the error term in the previous stage. The innovation involved in this approach is that it sufficiently and validly utilizes the useful residual information on an incomplete input variable condition. The proposed method was evaluated by experiments using a 2-year dataset of daily PM₁₀ (particles with a diameter of 10 μm or less) concentrations and SO₂ (sulfur dioxide) concentrations from four air pollution monitoring stations located in Taiyuan, China. The theoretical analysis and experimental results demonstrated that the forecasting accuracy of the proposed model is very promising. Copyright © 2014 Elsevier B.V. All rights reserved.

[Risk of deaths from cardiovascular diseases in Polish urban population associated with changes in maximal daily temperature].

PubMed

Rabczenko, Daniel; Wojtyniak, Bogdan; Kuchcik, Magdalena; Seroka, Wojciech

2009-01-01

The paper presents results of analysis of short-term effect of changes in maximal daily temperature on daily mortality from cardiovascular diseases in warm season in years 1999-2006. Analysis was carried out in six large Polish cities--Katowice, Kraków, Łódź, Poznań, Warszawa and Wrocław. Generalized additive models were used in the analysis. Potential confounding factors--long term changes of mortality, day of week and other meteorological factors (atmospheric pressure, humidity, mean wind speed) were taken into account during model building process. Analysis was done for two age groups--0-69 and 70 years and older. Significant, positive association between daily maximal temperature and risk of death from cardiovascular diseases was found only in older age group.

The influence of vegetation, mesoclimate and meteorology on urban atmospheric microclimates across a coastal to desert climate gradient.

PubMed

Crum, Steven M; Shiflett, Sheri A; Jenerette, G Darrel

2017-09-15

Many cities are increasing vegetation in part due to the potential for microclimate cooling. However, the magnitude of vegetation cooling and sensitivity to mesoclimate and meteorology are uncertain. To improve understanding of the variation in vegetation's influence on urban microclimates we asked: how do meso- and regional-scale drivers influence the magnitude and timing of vegetation-based moderation on summertime air temperature (T a ), relative humidity (RH) and heat index (HI) across dryland cities? To answer this question we deployed a network of 180 temperature sensors in summer 2015 over 30 high- and 30 low-vegetated plots in three cities across a coastal to inland to desert climate gradient in southern California, USA. In a followup study, we deployed a network of temperature and humidity sensors in the inland city. We found negative T a and HI and positive RH correlations with vegetation intensity. Furthermore, vegetation effects were highest in evening hours, increasing across the climate gradient, with reductions in T a and increases in RH in low-vegetated plots. Vegetation increased temporal variability of T a , which corresponds with increased nighttime cooling. Increasing mean T a was associated with higher spatial variation in T a in coastal cities and lower variation in inland and desert cities, suggesting a climate dependent switch in vegetation sensitivity. These results show that urban vegetation increases spatiotemporal patterns of microclimate with greater cooling in warmer environments and during nighttime hours. Understanding urban microclimate variation will help city planners identify potential risk reductions associated with vegetation and develop effective strategies ameliorating urban microclimate. Published by Elsevier Ltd.

Effects of anthropogenic heat release upon the urban climate in a Japanese megacity.

PubMed

Narumi, Daisuke; Kondo, Akira; Shimoda, Yoshiyuki

2009-05-01

This report presents results of investigations of the influence of anthropogenic heat release in Japanese megacity (Keihanshin district) upon the urban climate, using the energy database [Shimoda et al., 1999. Estimation and evaluation of artificial waste heat in urban area. Selected Papers from the Conference ICB-ICUC'99 WCASP-50 WMO/TD no. 1026] as a part of the land-surface boundary conditions of a mesoscale meteorological simulation model. The calculated results related to atmospheric temperature distribution were similar to observed values not only for daily averages but also for amplitudes and phases of diurnal change. To reproduce accurately, it is essential to reproduce urban characteristics such as an urban canopy and anthropogenic heat release in a fine resolution mesh. We attempted an analysis using current data for anthropogenic heat and under uniform heat release conditions, to investigate temporal and spatial characteristics in relation to the influence of anthropogenic heat release on the urban climate. The results of investigation into the influence of anthropogenic heat release on atmospheric temperature using current data indicate that the amount of heat released is lower at night than during the day, but the temperature rise is nearly 3 times greater. Results of investigation into the influence of anthropogenic heat release on wind systems using current data indicate that the onset of land breezes is delayed, particularly in a coastal area. Investigation into the temporal characteristics related to the influence of anthropogenic heat release under uniform heat release conditions showed a maximum influence on temperature during the predawn period.

Monitoring and assessment of the outdoor thermal comfort in Bucharest (Romania)

NASA Astrophysics Data System (ADS)

Cheval, Sorin; Ciobotaru, Ana-Maria; Andronache, Ion; Dumitrescu, Alexandru

2017-04-01

Bucharest is one of the European cities most at risk of being affected by meteorological hazards. Heat or cold waves, extreme temperature events, heavy rains or prolonged precipitation deficits are all-season phenomena, triggering damages, discomfort or even casualties. Temperature hazards may occur annually and challenge equally the public, local business and administration to find adequate solutions for securing the thermal comfort in the outdoor environment of the city. The accurate and fine resolution monitoring of the air temperature pledges for the comprehensive assessment of the thermal comfort in order to capture as much as possible the urban influence. This study uses sub-hourly temperature data (10-min temporal resolution) retrieved over the period November 2014 - November 2016 collected from nine sensors placed either in plain urban conditions or within the three meteorological stations of the national network which are currently monitoring the climate of Bucharest (Băneasa, Filaret, Afumați). The relative humidity was estimated based on the data available at the three stations placed in WMO standard conditions, and the 10-min values of 8 Thermal Comfort Indices were computed, namely: Heat Index, Humidex, Relative Strain Index, Scharlau, Summer Simmer Index, Physiological Equivalent Index, Temperature-Humidity Index, Thom Discomfort Index. The indices were analysed statistically, both individually and combined. Despite the short range of the available data, this study emphasizes clear spatial differentiations of the thermal comfort, in a very good agreement with the land cover and built zones of the city, while important variations were found in the temporal regime, due to large variations of the temperature values (e.g. >4 centigrade between consecutive hours or >15 centigrade between consecutive days). Ultimately, this study has revealed that the continuous monitoring of the urban climate, at fine temporal and spatial resolution, may deliver fundamental information for supporting the immediate measures and the long-term urban planning and the sustainable thermal comfort of the urban inhabitants. Acknowledgements: The urban meteorological network of Bucharest was developed within the project UCLIMESA (Urban Heat Island Monitoring under Present and Future Climate), in the framework of the Programme for Research-Development-Innovation for Space Technology and Advanced Research (STAR), administrated by the Romanian Space Agency. (STAR CDI Programme, contract no 92/2013, Contractor Romanian Spatial Agency). This work was supported by a grant of the University of Bucharest- "Spatial projection of the human pressure on forest ecosystems in Romania" (UB/1365)-and was supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNCS - UEFISCDI, project number PN-II-RU-TE-2014-4-0835-Development of the theory of the dynamic context by analyzing the role of the aridization in generating and amplifying the regressive phenomena from the territorial systems.

The use of RPAS in monitoring volume changes, subsidence and gas emissions from a landfill in Veneto Region, North east of Italy.

NASA Astrophysics Data System (ADS)

Busnardo, Enrico; Ravagnan, Riccardo; Castellarin, Nicola; Canella, Claudio; Gandolfo, Luca; Petrillo, Giovanni

2017-04-01

Public opinion consider landfills as a problematic waste disposal system. They are perceived as groundwater and air source of pollution, and unfortunately it is true. For this reason, Regional Environmental Agencies (ARPA) need data in order to figure out the potential pollution near landfills. Remotely Piloted Aircraft Systems (RPAS) with specific sensors, could be a better solution than traditional terrestrial sensors. They provide a better sampling at different altitudes. Therefore, a 3D diffusion gas model could be improved. This study case is about a solid urban waste landfill, located on the Venetian Po Plain in the south of the Veneto Region. The "electronic nose" on the RPAS, needs to be stand still at least 15 seconds while sampling. For this reason, in this study case a multicopter RPAS was used. The result was a 3D concentration map of pollutant gases. The map was related with meteorological data from a Regional meteorological station located near the landfill to identify the gas source. In the end, the study about the olfactory impact was made using the OdiGauss model, developed by the Agricultural and Environmental Sciences Department of Udine University. It was also compared with a simulation carried out with CALWin software.

Influence of sky view factor on outdoor thermal environment and physiological equivalent temperature

NASA Astrophysics Data System (ADS)

He, Xiaodong; Miao, Shiguang; Shen, Shuanghe; Li, Ju; Zhang, Benzhi; Zhang, Ziyue; Chen, Xiujie

2015-03-01

Sky view factor (SVF), which is an indicator of urban canyon geometry, affects the surface energy balance, local air circulation, and outdoor thermal comfort. This study focused on a continuous and long-term meteorological observation system to investigate the effects of SVF on outdoor thermal conditions and physiological equivalent temperature (PET) in the central business district (CBD) of Beijing (which is located within Chaoyang District), specifically addressed current knowledge gaps for SVF-PET relationships in cities with typical continental/microthermal climates. An urban sub-domain scale model and the RayMan model were used to diagnose wind fields and to calculate SVF and long-term PET, respectively. Analytical results show that the extent of shading contributes to variations in thermal perception distribution. Highly shaded areas (SVF <0.3) typically exhibit less frequent hot conditions during summer, while enduring longer periods of cold discomfort in winter than moderately shaded areas (0.3< SVF <0.5) and slightly shaded areas (SVF >0.5), and vice versa. Because Beijing has a monsoon-influenced humid continental climate with hot summers and long, cold, windy, and dry winters, a design project that ideally provides moderate shading should be planned to balance hot discomfort in summer and cold discomfort in winter, which effectively prolongs the comfort periods in outdoor spaces throughout the entire year. This research indicate that climate zone characteristics, urban environmental conditions, and thermal comfort requirements of residents must be accounted for in local-scale scientific planning and design, i.e., for urban canyon streets and residential estates.

A Reduced Form Model for Ozone Based on Two Decades of ...

EPA Pesticide Factsheets

A Reduced Form Model (RFM) is a mathematical relationship between the inputs and outputs of an air quality model, permitting estimation of additional modeling without costly new regional-scale simulations. A 21-year Community Multiscale Air Quality (CMAQ) simulation for the continental United States provided the basis for the RFM developed in this study. Predictors included the principal component scores (PCS) of emissions and meteorological variables, while the predictand was the monthly mean of daily maximum 8-hour CMAQ ozone for the ozone season at each model grid. The PCS form an orthogonal basis for RFM inputs. A few PCS incorporate most of the variability of emissions and meteorology, thereby reducing the dimensionality of the source-receptor problem. Stochastic kriging was used to estimate the model. The RFM was used to separate the effects of emissions and meteorology on ozone concentrations. by running the RFM with emissions constant (ozone dependent on meteorology), or constant meteorology (ozone dependent on emissions). Years with ozone-conducive meteorology were identified, and meteorological variables best explaining meteorology-dependent ozone were identified. Meteorology accounted for 19% to 55% of ozone variability in the eastern US, and 39% to 92% in the western US. Temporal trends estimated for original CMAQ ozone data and emission-dependent ozone were mostly negative, but the confidence intervals for emission-dependent ozone are much

Impact of High Resolution Land-Use Data in Meteorology and Air Quality Modeling Systems

EPA Science Inventory

Accurate land use information is important in meteorology for land surface exchanges, in emission modeling for emission spatial allocation, and in air quality modeling for chemical surface fluxes. Currently, meteorology, emission, and air quality models often use outdated USGS Gl...

Air pollution in the Benelux/Rhine-Ruhr area: Numerical simulations with a multi-scale regional chemistry-transport model

NASA Astrophysics Data System (ADS)

Memmesheimer, M.; Jakobs, H. J.; Wurzler, S.; Friese, E.; Piekorz, G.; Ebel, A.

2009-04-01

The Rhine-Ruhr area is a strongly industrialized region with about 10 Million inhabitants. It is one of the regions in Europe, which has the characteristics of a megacity with respect to population density, traffic, industry and environmental issues. The main centre of European steel production and the biggest inland port of the world is located in Duisburg, one of the major cities in the Rhine-Ruhr area. Together with the nearby urban agglomerations in the Benelux area including Brussels, Amsterdam and in particular Rotterdam as one of the most important sea-harbours of the world together with Singapore and Shanghai, it forms one of the regions in Europe heavily loaded with air pollutants as ozone, NO2 and particulate matter. Ammonia emissions outside the urban agglomerations but within the domain are also on a quite high level due to intense agricultural usage in Benelux, North-Rhine-Westphalia and lower Saxony. Therefore this area acts also as an important source region for gaseous precursors contributing to the formation of secondary particles in the atmosphere. The Benelux/Rhine-Ruhr area therefore has been selected within the framework of the recently established FP7 research project CityZen as one hot spot for detailed investigations of the past and current status of air pollution and its future development on different spatial and temporal scales. Some examples from numerical simulations with the regional multi-scale chemistry transport model EURAD for Central Europe and the Rhine-Ruhr area will be presented. The model calculates the transport, chemical transformations and deposition of trace constituents in the troposphere from the surface up to about 16 km using MM5 as meteorological driver, the RACM-MIM gas-phase chemistry and MADE-SORGAM for the treatment of particulate matter. Horizontal grid sizes are in the range of 100 km down to 1 km for heavily polluted urbanized areas within Benelux/Rhine-Ruhr. The planetary boundary layer is resolved by 15 layers below 3000 m, 8 layers cover the range from 3 km to 16 km. Emission projections have been used to calculate the future development of air pollution as well as the contribution of different sources to air pollution concentrations. The results are discussed with respect to different characteristic meteorological conditions which control the occurrence of air pollution episodes. Specific examples are heat waves as in summer 2003 leading to high values of photo-oxidants and episodes dominated by high pressure systems over Europe in fall and winter leading to high concentrations of particulate matter or NO2. Interannual variations due to changes of the meteorological conditions from year to year also will be discussed. It turned out that the impact of emission reduction on air pollution could be masked by the interannual variation of weather conditions which influence concentrations of air pollutants. Possible extensions and plans for the further development of the modelling system to include future changes of climate and consequently the coupling to the global scale are discussed with respect to CityZen.

Forecasting urban PM10 and PM2.5 pollution episodes in very stable nocturnal conditions and complex terrain using WRF-Chem CO tracer model

NASA Astrophysics Data System (ADS)

Saide, Pablo E.; Carmichael, Gregory R.; Spak, Scott N.; Gallardo, Laura; Osses, Axel E.; Mena-Carrasco, Marcelo A.; Pagowski, Mariusz

2011-05-01

This study presents a system to predict high pollution events that develop in connection with enhanced subsidence due to coastal lows, particularly in winter over Santiago de Chile. An accurate forecast of these episodes is of interest since the local government is entitled by law to take actions in advance to prevent public exposure to PM10 concentrations in excess of 150 μg m -3 (24 h running averages). The forecasting system is based on accurately simulating carbon monoxide (CO) as a PM10/PM2.5 surrogate, since during episodes and within the city there is a high correlation (over 0.95) among these pollutants. Thus, by accurately forecasting CO, which behaves closely to a tracer on this scale, a PM estimate can be made without involving aerosol-chemistry modeling. Nevertheless, the very stable nocturnal conditions over steep topography associated with maxima in concentrations are hard to represent in models. Here we propose a forecast system based on the WRF-Chem model with optimum settings, determined through extensive testing, that best describe both meteorological and air quality available measurements. Some of the important configurations choices involve the boundary layer (PBL) scheme, model grid resolution (both vertical and horizontal), meteorological initial and boundary conditions and spatial and temporal distribution of the emissions. A forecast for the 2008 winter is performed showing that this forecasting system is able to perform similarly to the authority decision for PM10 and better than persistence when forecasting PM10 and PM2.5 high pollution episodes. Problems regarding false alarm predictions could be related to different uncertainties in the model such as day to day emission variability, inability of the model to completely resolve the complex topography and inaccuracy in meteorological initial and boundary conditions. Finally, according to our simulations, emissions from previous days dominate episode concentrations, which highlights the need for 48 h forecasts that can be achieved by the system presented here. This is in fact the largest advantage of the proposed system.

Build-up and wash-off dynamics of atmospherically derived Cu, Pb, Zn and TSS in stormwater runoff as a function of meteorological characteristics.

PubMed

Murphy, Louise U; Cochrane, Thomas A; O'Sullivan, Aisling

2015-03-01

Atmospheric pollutants deposited on impermeable surfaces can be an important source of pollutants to stormwater runoff; however, modelling atmospheric pollutant loads in runoff has rarely been done, because of the challenges and uncertainties in monitoring their contribution. To overcome this, impermeable concrete boards (≈ 1m(2)) were deployed for 11 months in different locations within an urban area (industrial, residential and airside) throughout Christchurch, New Zealand, to capture spatially distributed atmospheric deposition loads in runoff over varying meteorological conditions. Runoff was analysed for total and dissolved Cu, Zn, Pb, and total suspended solids (TSS). Mixed-effect regression models were developed to simulate atmospheric pollutant loads in stormwater runoff. In addition, the models were used to explain the influence of different meteorological characteristics (e.g. antecedent dry days and rain depth) on pollutant build-up and wash-off dynamics. The models predicted approximately 53% to 69% of the variation in pollutant loads and were successful in predicting pollutant-load trends over time which can be useful for general stormwater planning processes. Results from the models illustrated the importance of antecedent dry days on pollutant build-up. Furthermore, results indicated that peak rainfall intensity and rain duration had a significant relationship with TSS and total Pb, whereas, rain depth had a significant relationship with total Cu and total Zn. This suggested that the pollutant speciation phase plays an important role in surface wash-off. Rain intensity and duration had a greater influence when the pollutants were predominantly in their particulate phase. Conversely, rain depth exerted a greater influence when a high fraction of the pollutants were predominantly in their dissolved phase. For all pollutants, the models were represented by a log-arctan relationship for pollutant build-up and a log-log relationship for pollutant wash-off. The modelling approach enables the site-specific relationships between individual pollutants and rainfall characteristics to be investigated. Copyright © 2014 Elsevier B.V. All rights reserved.

Observing the Vertical Extent of the Urban Boundary Layer Over Jersey City, NJ: A Diurnal and Seasonal Analysis

NASA Astrophysics Data System (ADS)

Dempsey, M. J.; Booth, J.; Arend, M.; Melecio-Vazquez, D.; Gonzalez, J.

2015-12-01

The atmospheric boundary remains one of the more difficult components of the climate system to classify. One of the most important characteristics is the boundary layer height, especially in urban settings. The current study examines the boundary layer height using the the New York City Meteorological Network or NYCMetNet. NYCMetNet is a network of weather stations, which report meteorological conditions in and around New York City, as part of the Optical Remote Sensing Laboratory of The City College of New York (ORSL). Of interest to this study is the data obtained from wind profiler station LSC01. The 915 MHz wind profiler is located 30m above the ground on the roof of the Liberty Science Center in Jersey City, NJ. It is a Vaisala Wind Profiler LAP 3000 with a wavelength of ~34cm, which means that the instrument responds primarily to Bragg backscattering. Can a seasonal urban boundary layer climatology be extrapolated from the data obtained from the wind profiler? What is the timing of boundary layer evolution and collapse over Jersey City? How effective is the profiler under cloudy skies and even in light rain or snow? This study examines the entire time period covered by the wind profile (2007 to present) and selects a series of clear days and a series of cloudy days. The top of the urban boundary layer is subjectively located from each half hour time stamp of signal to noise values. The urban boundary layer heights are recorded for clear and then cloudy days. Then the days are sorted seasonally (DJF, MAM, JJA, SON). A seasonal mean is calculated for every half hour time step. Finally a time series of seasonal urban boundary layer heights is constructed, and the timing of the urban boundary layer height maximum and time evolution and collapse of the boundary layer are generalized. A comparison is made against urban boundary layer heights obtained from Modern-Era Retrospective Analysis For Research And Applications (MERRA).

City Lights of Europe

NASA Technical Reports Server (NTRS)

2002-01-01

Growth in 'mega-cities' is altering the landscape and the atmosphere in such a way as to curtail normal photosynthesis. By using data from The Defense Meteorological Satellite Program's Operational Linescan System, researchers have been able to look at urban sprawl by monitoring the emission of light from cities at night. By overlaying these 'light maps' onto other data such as soil and vegetation maps, the research shows that urbanization can have a variable but measurable impact on photosynthetic productivity. For more information, read Bright Lights, Big City Image by the NASA GSFC Scientific Visualization Studio

Modeling ozone episodes in the Baltimore-Washington region

NASA Technical Reports Server (NTRS)

Ryan, William F.

1994-01-01

Surface ozone (O3) concentrations in excess of the National Ambient Air Quality Standard (NAAQS) continue to occur in metropolitan areas in the United States despite efforts to control emissions of O3 precursors. Future O3 control strategies will be based on results from modeling efforts that have just begun in many areas. Two initial questions that arise are model sensitivity to domain-specific conditions and the selection of episodes for model evaluation and control strategy development. For the Baltimore-Washington region (B-W), the presence of the Chesapeake Bay introduces a number of issues relevant to model sensitivity. In this paper, the specific questions of the determination of model volume (mixing height) for the Urban Airshed Model (UAM) is discussed and various alternative methods compared. For the latter question, several analytic approaches, Cluster Analysis and classification and Regression Tree (CART) analysis are undertaken to determine meteorological conditions associated with severe O3 events in the B-W domain.

Open Source Tools for Numerical Simulation of Urban Greenhouse Gas Emissions

NASA Astrophysics Data System (ADS)

Nottrott, A.; Tan, S. M.; He, Y.

2016-12-01

There is a global movement toward urbanization. Approximately 7% of the global population lives in just 28 megacities, occupying less than 0.1% of the total land area used by human activity worldwide. These cities contribute a significant fraction of the global budget of anthropogenic primary pollutants and greenhouse gasses. The 27 largest cities consume 9.9%, 9.3%, 6.7% and 3.0% of global gasoline, electricity, energy and water use, respectively. This impact motivates novel approaches to quantify and mitigate the growing contribution of megacity emissions to global climate change. Cities are characterized by complex topography, inhomogeneous turbulence, and variable pollutant source distributions. These features create a scale separation between local sources and urban scale emissions estimates known as the Grey-Zone. Modern computational fluid dynamics (CFD) techniques provide a quasi-deterministic, physically based toolset to bridge the scale separation gap between source level dynamics, local measurements, and urban scale emissions inventories. CFD has the capability to represent complex building topography and capture detailed 3D turbulence fields in the urban boundary layer. This presentation discusses the application of OpenFOAM to urban CFD simulations of natural gas leaks in cities. OpenFOAM is an open source software for advanced numerical simulation of engineering and environmental fluid flows. When combined with free or low cost computer aided drawing and GIS, OpenFOAM generates a detailed, 3D representation of urban wind fields. OpenFOAM was applied to model methane (CH4) emissions from various components of the natural gas distribution system, to investigate the impact of urban meteorology on mobile CH4 measurements. The numerical experiments demonstrate that CH4 concentration profiles are highly sensitive to the relative location of emission sources and buildings. Sources separated by distances of 5-10 meters showed significant differences in vertical dispersion of the plume due to building wake effects. The OpenFOAM flow fields were combined with an inverse, stochastic dispersion model to quantify and visualize the sensitivity of point sensors to upwind sources in various built environments.

Assessment of hydrogen sulfide emission from a sewage treatment plant using AERMOD.

PubMed

Baawain, Mahad; Al-Mamun, Abdullah; Omidvarborna, Hamid; Al-Jabri, Abdullah

2017-06-01

Air quality modeling plays an important role in prediction of air pollutants in urban areas. Moreover, it is also an essential component to make crucial decisions in environmental management. In this study, environmental protection agency (EPA) regulatory model (AERMOD) was implemented in order to assess the urban air quality in the city of Muscat, Sultanate of Oman. Dispersion modeling was employed for the prediction of hydrogen sulfide (H 2 S) emissions, a neighborhood claimed issue, from Al-Ansab sewage treatment plant (STP). Meteorological, elevation data, and H 2 S survey results were implemented into the model. From the site survey study, four different H 2 S emission sources were identified as sewage tanker connection points, biofilter, old odor control unit (OCU), and open channels of raw sewage. It was observed that based on maximum 24-h analysis, the ground level concentration outside the STP exceeded the concentration limit, 40 μg/m 3 , recommended by the local regulating agency in Oman. By applying a sensitivity analysis study, the locations with the highest predicted H 2 S levels were identified. The most affected area in the worst-case scenario was the nearby expressway with 450.9 μg/m 3 of H 2 S. The highest ground level concentration of H 2 S was detected in March, while the lowest was measured in December. The model also predicted that the impact of odor nuisance is greater at the summer season than that of other seasons due to the elevated temperatures. The study revealed an adverse environmental impact from the STPs on urban air quality, which may pose a threat to the public health.

A spatial-temporal regression model to predict daily outdoor residential PAH concentrations in an epidemiologic study in Fresno, CA

NASA Astrophysics Data System (ADS)

Noth, Elizabeth M.; Hammond, S. Katharine; Biging, Gregory S.; Tager, Ira B.

2011-05-01

BackgroundPolycyclic aromatic hydrocarbons (PAHs) are generated as a byproduct of combustion, and are associated with respiratory symptoms and increased risk of asthma attacks. ObjectivesTo assign daily, outdoor exposures to participants in the Fresno Asthmatic Children's Environment Study (FACES) using land use regression models for the sum of 4-, 5- and 6-ring PAHs (PAH456). MethodsPAH data were collected daily at the EPA Supersite in Fresno, CA from 10/2000 through 2/2007. From 2/2002 to 2/2003, intensive air pollution sampling was conducted at 83 homes of participants in the FACES study. These measurement data were combined with meteorological data, source data, and other spatial variables to form a land use regression model to assign daily exposure at all FACES homes for all years of the study (2001-2008). ResultsThe model for daily, outdoor residential PAH456 concentrations accounted for 80% of the between-home variability and 18% of the within-home variability. Both temporal and spatial variables were significant in the model. Traffic characteristics and home heating fuel were the main spatial explanatory variables. ConclusionsBecause spatial and temporal distributions of PAHs vary on an intra-urban scale, the location of the child's home within the urban setting plays an important role in the level of exposure that each child has to PAHs.

Quantification of Methane Source Locations and Emissions in AN Urban Setting

NASA Astrophysics Data System (ADS)

Crosson, E.; Richardson, S.; Tan, S. M.; Whetstone, J.; Bova, T.; Prasad, K. R.; Davis, K. J.; Phillips, N. G.; Turnbull, J. C.; Shepson, P. B.; Cambaliza, M. L.

2011-12-01

The regulation of methane emissions from urban sources such as landfills and waste-water treatment facilities is currently a highly debated topic in the US and in Europe. This interest is fueled, in part, by recent measurements indicating that urban emissions are a significant source of Methane (CH4) and in fact may be substantially higher than current inventory estimates(1). As a result, developing methods for locating and quantifying emissions from urban methane sources is of great interest to industries such as landfill and wastewater treatment facility owners, watchdog groups, and the governmental agencies seeking to evaluate or enforce regulations. In an attempt to identify major methane source locations and emissions in Boston, Indianapolis, and the Bay Area, systematic measurements of CH4 concentrations and meteorology data were made at street level using a vehicle mounted cavity ringdown analyzer. A number of discrete sources were detected at concentration levels in excess of 15 times background levels. Using Gaussian plume models as well as tomographic techniques, methane source locations and emission rates will be presented. In addition, flux chamber measurements of discrete sources such as those found in natural gas leaks will also be presented. (1) Wunch, D., P.O. Wennberg, G.C. Toon, G. Keppel-Aleks, and Y.G. Yavin, Emissions of Greenhouse Gases from a North American Megacity, Geophysical Research Letters, Vol. 36, L15810, doi:10.1029/2009GL)39825, 2009.

Meteorological factors for PM10 concentration levels in Northern Spain

NASA Astrophysics Data System (ADS)

Santurtún, Ana; Mínguez, Roberto; Villar-Fernández, Alejandro; González Hidalgo, Juan Carlos; Zarrabeitia, María Teresa

2013-04-01

Atmospheric particulate matter (PM) is made up of a mixture of solid and aqueous species which enter the atmosphere by anthropogenic and natural pathways. The levels and composition of ambient air PM depend on the climatology and on the geography (topography, soil cover, proximity to arid zones or to the coast) of a given region. Spain has particular difficulties in achieving compliance with the limit values established by the European Union (based on recommendations from the World Health Organization) for particulate matter on the order of 10 micrometers of diameter or less (PM10), but not only antropogenical emissions are responsible for this: some studies show that PM10 concentrations originating from these kinds of sources are similar to what is found in other European countries, while some of the geographical features of the Iberian Peninsula (such as African mineral dust intrusion, soil aridity or rainfall) are proven to be a factor for higher PM concentrations. This work aims to describe PM10 concentration levels in Cantabria (Northern Spain) and their relationship with the following meteorological variables: rainfall, solar radiation, temperature, barometric pressure and wind speed. Data consists of daily series obtained from hourly data records for the 2000-2010 period, of PM10 concentrations from 4 different urban-background stations, and daily series of the meteorological variables provided by Spanish National Meteorology Agency. The method used for establishing the relationships between these variables consists of several steps: i) fitting a non-stationary probability density function for each variable accounting for long-term trends, seasonality during the year and possible seasonality during the week to distinguish between work and weekend days, ii) using the marginal distribution function obtained, transform the time series of historical values of each variable into a normalized Gaussian time series. This step allows using consistently time series models, iii) fitting of a times series model (Autoregressive moving average, ARMA) to the transformed historical values in order to eliminate the temporal autocorrelation structure of each stochastic process, obtaining a white noise for each variable, and finally, iv) the calculation of cross correlations between white noises at different time lags. These cross correlations allow characterization of the true correlation between signals, avoiding the problems induced by data scaling or autocorrelations inherent to each signal. Results provide the relationship and possible contribution to PM10 concentration levels associated with each meteorological variable. This information can be used to improve PM10 concentration levels forecasting using existing meteorological forecasts.

Daily ambient air pollution metrics for five cities: Evaluation of data-fusion-based estimates and uncertainties

NASA Astrophysics Data System (ADS)

Friberg, Mariel D.; Kahn, Ralph A.; Holmes, Heather A.; Chang, Howard H.; Sarnat, Stefanie Ebelt; Tolbert, Paige E.; Russell, Armistead G.; Mulholland, James A.

2017-06-01

Spatiotemporal characterization of ambient air pollutant concentrations is increasingly relying on the combination of observations and air quality models to provide well-constrained, spatially and temporally complete pollutant concentration fields. Air quality models, in particular, are attractive, as they characterize the emissions, meteorological, and physiochemical process linkages explicitly while providing continuous spatial structure. However, such modeling is computationally intensive and has biases. The limitations of spatially sparse and temporally incomplete observations can be overcome by blending the data with estimates from a physically and chemically coherent model, driven by emissions and meteorological inputs. We recently developed a data fusion method that blends ambient ground observations and chemical-transport-modeled (CTM) data to estimate daily, spatially resolved pollutant concentrations and associated correlations. In this study, we assess the ability of the data fusion method to produce daily metrics (i.e., 1-hr max, 8-hr max, and 24-hr average) of ambient air pollution that capture spatiotemporal air pollution trends for 12 pollutants (CO, NO2, NOx, O3, SO2, PM10, PM2.5, and five PM2.5 components) across five metropolitan areas (Atlanta, Birmingham, Dallas, Pittsburgh, and St. Louis), from 2002 to 2008. Three sets of comparisons are performed: (1) the CTM concentrations are evaluated for each pollutant and metropolitan domain, (2) the data fusion concentrations are compared with the monitor data, (3) a comprehensive cross-validation analysis against observed data evaluates the quality of the data fusion model simulations across multiple metropolitan domains. The resulting daily spatial field estimates of air pollutant concentrations and uncertainties are not only consistent with observations, emissions, and meteorology, but substantially improve CTM-derived results for nearly all pollutants and all cities, with the exception of NO2 for Birmingham. The greatest improvements occur for O3 and PM2.5. Squared spatiotemporal correlation coefficients range between simulations and observations determined using cross-validation across all cities for air pollutants of secondary and mixed origins are R2 = 0.88-0.93 (O3), 0.81-0.89 (SO4), 0.67-0.83 (PM2.5), 0.52-0.72 (NO3), 0.43-0.80 (NH4), 0.32-0.51 (OC), and 0.14-0.71 (PM10). Results for relatively homogeneous pollutants of secondary origin, tend to be better than those for more spatially heterogeneous (larger spatial gradients) pollutants of primary origin (NOx, CO, SO2 and EC). Generally, background concentrations and spatial concentration gradients reflect interurban airshed complexity and the effects of regional transport, whereas daily spatial pattern variability shows intra-urban consistency in the fused data. With sufficiently high CTM spatial resolution, traffic-related pollutants exhibit gradual concentration gradients that peak toward the urban centers. Ambient pollutant concentration uncertainty estimates for the fused data are both more accurate and smaller than those for either the observations or the model simulations alone.

Air pollution from future giant jetports

NASA Technical Reports Server (NTRS)

Fay, J. A.

1970-01-01

Because aircraft arrive and depart in a generally upwind direction, the pollutants are deposited in a narrow corridor extending downwind of the airport. Vertical mixing in the turbulent atmosphere will not dilute such a trail, since the pollutants are distributed vertically during the landing and take-off operations. As a consequence, airport pollution may persist twenty to forty miles downwind without much attenuation. Based on this simple meteorological model, calculations of the ambient levels of nitric oxide and particulates to be expected downwind of a giant jetport show them to be about equal to those in present urban environments. These calculations are based on measured emission rates from jet engines and estimates of aircraft performance and traffic for future jetports.

Soil Water Balance and Vegetation Dynamics in two Water-limited Mediterranean Ecosystem on Sardinia under past and future climate change

NASA Astrophysics Data System (ADS)

Corona, R.; Montaldo, N.; Albertson, J. D.

2016-12-01

Water limited conditions strongly impacts soil and vegetation dynamics in Mediterranean regions, which are commonly heterogeneous ecosystems, characterized by inter-annual rainfall variability, topography variability and contrasting plant functional types (PFTs) competing for water use. Historical human influences (e.g., deforestation, urbanization) further altered these ecosystems. Sardinia island is a representative region of Mediterranean ecosystems. It is low urbanized except some plan areas close to the main cities where main agricultural activities are concentrated. Two contrasting case study sites are within the Flumendosa river basin (1700 km2). The first site is a typical grassland on an alluvial plan valley (soil depth > 2m) while the second is a patchy mixture of Mediterranean vegetation species (mainly wild olive trees and C3 herbaceous) that grow in a soil bounded from below by a rocky layer of basalt, partially fractured (soil depth 15 - 40 cm). In both sites land-surface fluxes and CO2 fluxes are estimated by the eddy correlation technique while soil moisture was continuously estimated with water content reflectometers, and periodically leaf area index (LAI) was estimated. The following objectives are addressed:1) pointing out the dynamics of land surface fluxes, soil moisture, CO2 and vegetation cover for two contrasting water-limited ecosystems; 2) assess the impact of the soil depth and type on the CO2 and water balance dynamics; 3) evaluate the impact of past and future climate change scenarios on the two contrasting ecosystems. For reaching the objectives an ecohydrologic model that couples a vegetation dynamic model (VDM), and a 3-component (bare soil, grass and woody vegetation) land surface model (LSM) has been used. Historical meteorological data are available from 1922 and hydro-meteorological scenarios are then generated using a weather generator. The VDM-LSM model predict soil water balance and vegetation dynamics for the generated hydrometeorological scenarios in the two contrasting ecosystems. Results demonstrate that vegetation dynamics are influenced by the inter-annual variability of atmospheric forcing, with vegetation density changing significantly according to seasonal rainfall amount. At the same time the vegetation dynamics affect the soil water balance.

Phase 1 Free Air CO2 Enrichment Model-Data Synthesis (FACE-MDS): Meteorological Data

DOE Data Explorer

Norby, R. J.; Oren, R.; Boden, T. A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL); De Kauwe, M. G.; Kim, D.; Medlyn, B. E.; Riggs, J. S.; Tharp, M. L.; Walker, A. P.; Yang, B.; Zaehle, S.

2015-01-01

These datasets comprise the meteorological, CO2 and N deposition data used to run models for the Duke and Oak Ridge FACE experiments. Phase 1 datasets are reproduced here for posterity and reproducibility although these meteorological datasets are superseded by the Phase 2 datasets. If you would like to use the meteorological datasets to run your own model or for any other purpose please use the Phase 2 datasets.

Next generation paradigm for urban pluvial flood modelling, prediction, management and vulnerability reduction - Interaction between RainGain and Blue Green Dream projects

NASA Astrophysics Data System (ADS)

Maksimovic, C.

2012-04-01

The effects of climate change and increasing urbanisation call for a new paradigm for efficient planning, management and retrofitting of urban developments to increase resilience to climate change and to maximize ecosystem services. Improved management of urban floods from all sources in required. Time scale for well documented fluvial and coastal floods allows for timely response but surface (pluvial) flooding caused by intense local storms had not been given appropriate attention, Pitt Review (UK). Urban surface floods predictions require fine scale data and model resolutions. They have to be tackled locally by combining central inputs (meteorological services) with the efforts of the local entities. Although significant breakthrough in modelling of pluvial flooding was made there is a need to further enhance short term prediction of both rainfall and surface flooding. These issues are dealt with in the EU Iterreg project Rain Gain (RG). Breakthrough in urban flood mitigation can only be achieved by combined effects of advanced planning design, construction and management of urban water (blue) assets in interaction with urban vegetated areas' (green) assets. Changes in design and operation of blue and green assets, currently operating as two separate systems, is urgently required. Gaps in knowledge and technology will be introduced by EIT's Climate-KIC Blue Green Dream (BGD) project. The RG and BGD projects provide synergy of the "decoupled" blue and green systems to enhance multiple benefits to: urban amenity, flood management, heat island, biodiversity, resilience to drought thus energy requirements, thus increased quality of urban life at lower costs. Urban pluvial flood management will address two priority areas: Short Term rainfall Forecast and Short term flood surface forecast. Spatial resolution of short term rainfall forecast below 0.5 km2 and lead time of a few hours are needed. Improvements are achievable by combining data sources of raingauge networks with C-Band and X-Band radars with NWP and pluvial flood prediction models. The RG project deals with the merging and providing synergy of these technologies. Combined effects of BG technologies can totally reduce the risk of surface flooding for low return period events and up to 50-80% for high return periods. Demonstration technology testing sites for both BGD and RG projects will be established in 5 participating countries. Decision Support Systems will enhance full scale implementation of both BGD and RG project deliverables. A BGD efficiency rating scheme and training guidelines and e-learning tools will be developed. Experimental/demo sites for BDG and RG technology development and testing in Rotterdam, Paris, Berlin, Leuven and London and the expected results with concepts of RG and BGD projects and the initial results will be presented in the paper.

Unraveling the Complexity of Wildland Urban Interface Fires.

PubMed

Mahmoud, Hussam; Chulahwat, Akshat

2018-06-18

Recent wildland urban interface fires have demonstrated the unrelenting destructive nature of these events and have called for an urgent need to address the problem. The Wildfire paradox reinforces the ideology that forest fires are inevitable and are actually beneficial; therefore focus should to be shifted towards minimizing potential losses to communities. This requires the development of vulnerability-based frameworks that can be used to provide holistic understanding of risk. In this study, we devise a probabilistic approach for quantifying community vulnerability to wildfires by applying concepts of graph theory. A directed graph for community in question is developed to model wildfire inside a community by incorporating different fire propagation modes. The model accounts for relevant community-specific characteristics including wind conditions, community layout, individual structural features, and the surrounding wildland vegetation. We calibrate the framework to study the infamous 1991 Oakland fire in an attempt to unravel the complexity of community fires. We use traditional centrality measures to identify critical behavior patterns and to evaluate the effect of fire mitigation strategies. Unlike current practice, the results are shown to be community-specific with substantial dependency of risk on meteorological conditions, environmental factors, and community characteristics and layout.

Modeling the influence of biogenic volatile organic compound emissions on ozone concentration during summer season in the Kinki region of Japan

NASA Astrophysics Data System (ADS)

Bao, Hai; Shrestha, Kundan Lal; Kondo, Akira; Kaga, Akikazu; Inoue, Yoshio

2010-01-01

Tropospheric ozone adversely affects human health and vegetation, and biogenic volatile organic compound (BVOC) emission has potential to influence ozone concentration in summer season. In this research, the standard emissions of isoprene and monoterpene from the vegetation of the Kinki region of Japan, estimated from growth chamber experiments, were converted into hourly emissions for July 2002 using the temperature and light intensity data obtained from results of MM5 meteorological model. To investigate the effect of BVOC emissions on ozone production, two ozone simulations for one-month period of July 2002 were carried out. In one simulation, hourly BVOC emissions were included (BIO), while in the other one, BVOC emissions were not considered (NOBIO). The quantitative analyses of the ozone results clearly indicate that the use of spatio-temporally varying BVOC emission improves the prediction of ozone concentration. The hourly differences of monthly-averaged ozone concentrations between BIO and NOBIO had the maximum value of 6 ppb at 1400 JST. The explicit difference appeared in urban area, though the place where the maximum difference occurred changed with time. Overall, BVOC emissions from the forest vegetation strongly affected the ozone generation in the urban area.

Machine learning methods reveal the temporal pattern of dengue incidence using meteorological factors in metropolitan Manila, Philippines.

PubMed

Carvajal, Thaddeus M; Viacrusis, Katherine M; Hernandez, Lara Fides T; Ho, Howell T; Amalin, Divina M; Watanabe, Kozo

2018-04-17

Several studies have applied ecological factors such as meteorological variables to develop models and accurately predict the temporal pattern of dengue incidence or occurrence. With the vast amount of studies that investigated this premise, the modeling approaches differ from each study and only use a single statistical technique. It raises the question of whether which technique would be robust and reliable. Hence, our study aims to compare the predictive accuracy of the temporal pattern of Dengue incidence in Metropolitan Manila as influenced by meteorological factors from four modeling techniques, (a) General Additive Modeling, (b) Seasonal Autoregressive Integrated Moving Average with exogenous variables (c) Random Forest and (d) Gradient Boosting. Dengue incidence and meteorological data (flood, precipitation, temperature, southern oscillation index, relative humidity, wind speed and direction) of Metropolitan Manila from January 1, 2009 - December 31, 2013 were obtained from respective government agencies. Two types of datasets were used in the analysis; observed meteorological factors (MF) and its corresponding delayed or lagged effect (LG). After which, these datasets were subjected to the four modeling techniques. The predictive accuracy and variable importance of each modeling technique were calculated and evaluated. Among the statistical modeling techniques, Random Forest showed the best predictive accuracy. Moreover, the delayed or lag effects of the meteorological variables was shown to be the best dataset to use for such purpose. Thus, the model of Random Forest with delayed meteorological effects (RF-LG) was deemed the best among all assessed models. Relative humidity was shown to be the top-most important meteorological factor in the best model. The study exhibited that there are indeed different predictive outcomes generated from each statistical modeling technique and it further revealed that the Random forest model with delayed meteorological effects to be the best in predicting the temporal pattern of Dengue incidence in Metropolitan Manila. It is also noteworthy that the study also identified relative humidity as an important meteorological factor along with rainfall and temperature that can influence this temporal pattern.

Projecting Future Urbanization with Prescott College's Spatial Growth Model to Promote Environmental Sustainability and Smart Growth, A Case Study in Atlanta, Georgia

NASA Technical Reports Server (NTRS)

Estes, Maurice G., Jr.; Crosson, William; Limaye, Ashutosh; Johnson, Hoyt; Quattrochi, Dale; Lapenta, William; Khan, Maudood

2006-01-01

Planning is an integral element of good management and necessary to anticipate events not merely respond to them. Projecting the quantity and spatial distribution of urban growth is essential to effectively plan for the delivery of city services and to evaluate potential environmental impacts. The major drivers of growth in large urban areas are increasing population, employment opportunities, and quality of life attractors such as a favorable climate and recreation opportunities. The spatial distribution of urban growth is dictated by the amount and location of developable land, topography, energy and water resources, transportation network, climate change, and the existing land use configuration. The Atlanta region is growing very rapidly both in population and the consumption of forestland or low-density residential development. Air pollution and water availability are significant ongoing environmental issues. The Prescott Spatial Growth Model (SGM) was used to make growth projections for the metropolitan Atlanta region to 2010,2020 and 2030 and results used for environmental assessment in both business as usual and smart growth scenarios. The Prescott SGM is a tool that uses an ESRI ArcView extension and can be applied at the parcel level or more coarse spatial scales and can accommodate a wide range of user inputs to develop any number of growth rules each of which can be weighted depending on growth assumptions. These projections were used in conjunction with meteorological and air quality models to evaluate future environmental impacts. This presentation will focus on the application of the SGM to the 13-County Atlanta Regional Commission planning jurisdiction as a case study. The SGM will be described, including how rule sets are developed and the decision process for allocation of future development to available land use categories. Data inputs required to effectively run the model will be discussed. Spatial growth projections for ten, twenty, and thirty year planning horizons will be presented and results discussed, including regional climate and air quality impacts.

Resolving uncertainties in the urban air quality, climate, and vegetation nexus through citizen science, satellite imagery, and atmospheric modeling

NASA Astrophysics Data System (ADS)

Jenerette, D.; Wang, J.; Chandler, M.; Ripplinger, J.; Koutzoukis, S.; Ge, C.; Castro Garcia, L.; Kucera, D.; Liu, X.

2017-12-01

Large uncertainties remain in identifying the distribution of urban air quality and temperature risks across neighborhood to regional scales. Nevertheless, many cities are actively expanding vegetation with an expectation to moderate both climate and air quality risks. We address these uncertainties through an integrated analysis of satellite data, atmospheric modeling, and in-situ environmental sensor networks maintained by citizen scientists. During the summer of 2017 we deployed neighborhood-scale networks of air temperature and ozone sensors through three campaigns across urbanized southern California. During each five-week campaign we deployed six sensor nodes that included an EPA federal equivalent method ozone sensor and a suite of meteorological sensors. Each node was further embedded in a network of 100 air temperature sensors that combined a randomized design developed by the research team and a design co-created by citizen scientists. Between 20 and 60 citizen scientists were recruited for each campaign, with local partners supporting outreach and training to ensure consistent deployment and data gathering. We observed substantial variation in both temperature and ozone concentrations at scales less than 4km, whole city, and the broader southern California region. At the whole city scale the average spatial variation with our ozone sensor network just for city of Long Beach was 26% of the mean, while corresponding variation in air temperature was only 7% of the mean. These findings contrast with atmospheric model estimates of variation at the regional scale of 11% and 1%. Our results show the magnitude of fine-scale variation underestimated by current models and may also suggest scaling functions that can connect neighborhood and regional variation in both ozone and temperature risks in southern California. By engaging citizen science with high quality sensors, satellite data, and real-time forecasting, our results help identify magnitudes of climate and air quality risk variation across scales and can guide individual decisions and urban policies surrounding vegetation to moderate these risks.

Mapping air quality zones for coastal urban centers.

PubMed

Freeman, Brian; Gharabaghi, Bahram; Thé, Jesse; Munshed, Mohammad; Faisal, Shah; Abdullah, Meshal; Al Aseed, Athari

2017-05-01

This study presents a new method that incorporates modern air dispersion models allowing local terrain and land-sea breeze effects to be considered along with political and natural boundaries for more accurate mapping of air quality zones (AQZs) for coastal urban centers. This method uses local coastal wind patterns and key urban air pollution sources in each zone to more accurately calculate air pollutant concentration statistics. The new approach distributes virtual air pollution sources within each small grid cell of an area of interest and analyzes a puff dispersion model for a full year's worth of 1-hr prognostic weather data. The difference of wind patterns in coastal and inland areas creates significantly different skewness (S) and kurtosis (K) statistics for the annually averaged pollutant concentrations at ground level receptor points for each grid cell. Plotting the S-K data highlights grouping of sources predominantly impacted by coastal winds versus inland winds. The application of the new method is demonstrated through a case study for the nation of Kuwait by developing new AQZs to support local air management programs. The zone boundaries established by the S-K method were validated by comparing MM5 and WRF prognostic meteorological weather data used in the air dispersion modeling, a support vector machine classifier was trained to compare results with the graphical classification method, and final zones were compared with data collected from Earth observation satellites to confirm locations of high-exposure-risk areas. The resulting AQZs are more accurate and support efficient management strategies for air quality compliance targets effected by local coastal microclimates. A novel method to determine air quality zones in coastal urban areas is introduced using skewness (S) and kurtosis (K) statistics calculated from grid concentrations results of air dispersion models. The method identifies land-sea breeze effects that can be used to manage local air quality in areas of similar microclimates.

Analyzing the Velocity of Urban Dynamic Over Northeastern China Using Dmsp-Ols Night-Time Lights

NASA Astrophysics Data System (ADS)

Zhou, Y.

2017-09-01

Stable night-time lights (NTL) data from the Defense Meteorological Satellite Program Operational Line-scan System (DMSPOLS) can serve as a good proxy for anthropogenic development. Here DMSP-OLS NTL data was used to detect the urban development status in northeastern China. The spatial and temporal gradients are combined to depict the velocity of urban expanding process. This velocity index represents the instantaneous local velocity along the Earth's surface needed to maintain constant NTL condition, and has a mean of 0.36 km/yr for northeastern China. The velocity change of NTL is lower in the urban center and its near regions, and the suburbs show a relatively high value. The connecting zones between satellite cities and metropolis have also a rapid rate of NTL evolution. The dynamic process of urbanization over the study area is mainly in a manner of spreading from urban cores to edges. The rank size of the velocity for the prefectures is analyzed and a long tail distribution is found. The velocity index can provide insights for the future pattern of urban sprawl.

Evaluation of the thermal structure in an urban street canyon: field measurements and model simulation

NASA Astrophysics Data System (ADS)

Giovannini, L.; de Franceschi, M.; Zardi, D.

2009-04-01

The results of a research project, aiming at providing tools and criteria to evaluate the temperature field inside an urban street canyon, are presented. Temperature measurements have been carried out, both in summertime and in wintertime, inside a North-South oriented urban canyon in the city of Trento (Italy) in the Alps, with sensors placed at various heights on the front of buildings flanking the street and on top of traffic lights in the middle of the canyon. The results have been analyzed in comparison with data from an automated weather station placed close to the street canyon, at 33 m above ground level and taken as a reference for the above roof-top level. During sunny days a well defined cycle was identified in the daily evolution of air temperature measured by the sensors inside the urban canyon, which was primarily influenced by direct solar radiation. As expected, during the morning the East-facing sensors warmed up faster than the other ones, while in the afternoon the West-facing instruments were the warmest. In most cases the air temperature inside the canyon was higher than above roof level, with differences depending on weather conditions and hour of the day. The dataset allowed to characterize the microclimate of the urban canopy layer and provided a basis for testing the ability of a simple numerical model to simulate the thermal structure inside the urban canyon. The model displays the following characteristics: assignment of distinct surface types (road, walls and roofs), in order to better simulate their physical properties; computation of radiative exchanges inside the canyon based on view factors between the different surfaces and explicitly treating both the solar reflections and the shadows; storage heat flux simulated by means of the heat conduction equation. The model requires as input the geometry parameters of the street and the values of meteorological variables measured above roof level. The main outputs are the heat fluxes determined by the surface energy balance (road, building fronts), the surface temperatures and the average air temperature inside the urban canyon. The comparison between the results of the model and the measurements made during the field experiments displays a good agreement, with an average error of 0.3-0.4 °C on the evaluation of the mean air temperature inside the street canyon. This result is remarkable, especially considering the low level of complexity of the numerical code and the simplifying assumptions made.

Characterization, source identification and apportionment of selected metals in TSP in an urban atmosphere.

PubMed

Shah, Munir H; Shaheen, N; Jaffar, M

2006-03-01

To understand the metal distribution characteristics in the atmosphere of urban Islamabad, total suspended particulate (TSP) samples were collected on daily 12 h basis, at Quaid-i-Azam University campus, using high volume sampler. The TSP samples were treated with HNO(3)/HClO(4) based wet digestion method for the quantification of eight selected metals; Fe, Zn, Pb, Mn, Cr, Co, Ni and Cd by FAAS method. The monitoring period ran from June 2001 to January 2002, with a total of 194 samples collected on cellulose filters. Effects of different meteorological conditions such as temperature, relative humidity, wind speed and wind direction on selected metal levels were interpreted by means of multivariate statistical approach. Enhanced metal levels for Fe (930 ng/m(3)), Zn (542 ng/m(3)) and Pb (210 ng/m(3)) were found on the mean scale while Mn, Cr, Co and Ni emerged as minor contributors. Statistical correlation study was also conducted and a strong correlation was observed between Pb-Cr (r=0.611). The relative humidity showed some significant influence on atmospheric metal distribution while other meteorological parameters showed weak relationship with TSP metal levels. Regarding the origin of sources of heavy metals in TSP, the statistical procedure identified three source profiles; automobile emissions, industrial/metallurgical units, and natural soil dust. The metal levels were also compared with those reported for other parts of the world which showed that the metal levels in urban atmosphere of Islamabad are in exceedence than those of European industrial and urban sites while comparable with some Asian sites.

Endotoxins in urban air in Stockholm, Sweden

NASA Astrophysics Data System (ADS)

Nilsson, S.; Merritt, A. S.; Bellander, T.

2011-01-01

Endotoxins, i.e. components originating from the outer membrane in the cell wall of Gram-negative bacteria, activate the human immune system, which may result in airway symptoms such as shortness of breath and airway inflammation. Endotoxins are present in the environment, both outdoors and indoors, and stay airborne for a long time. In order to investigate the levels of endotoxins in urban air and the influence of traffic and meteorological factors, particles (PM 10 and PM 2.5) were collected at five sites in Stockholm, Sweden on four occasions per site between May and September 2009. Endotoxins were extracted from the filters and analysis was conducted with the Limulus Amebocyte Lysate (LAL)-assay. Endotoxins were present in urban air in Stockholm, albeit in low levels, and were similar to levels found in urban areas outside Sweden. To our knowledge, this is the northernmost location where endotoxins have been measured. The endotoxin levels found in PM 10 ranged from 0.020 to 0.107 EU m -3 with a geometric mean of 0.050 EU m -3 and the levels found in PM 2.5 ranged from 0.005 to 0.064 EU m -3 with a geometric mean of 0.015 EU m -3. No obvious effects of traffic or meteorological factors on endotoxin levels were observed, although a moderate correlation could be seen with soot. The small number of sampling sites is however a shortcoming of the present study. In future studies, more sites and sampling during all seasons would be preferable in order to get a better picture of the influence of different sources on endotoxin levels.

Optimization of artificial neural network models through genetic algorithms for surface ozone concentration forecasting.

PubMed

Pires, J C M; Gonçalves, B; Azevedo, F G; Carneiro, A P; Rego, N; Assembleia, A J B; Lima, J F B; Silva, P A; Alves, C; Martins, F G

2012-09-01

This study proposes three methodologies to define artificial neural network models through genetic algorithms (GAs) to predict the next-day hourly average surface ozone (O(3)) concentrations. GAs were applied to define the activation function in hidden layer and the number of hidden neurons. Two of the methodologies define threshold models, which assume that the behaviour of the dependent variable (O(3) concentrations) changes when it enters in a different regime (two and four regimes were considered in this study). The change from one regime to another depends on a specific value (threshold value) of an explanatory variable (threshold variable), which is also defined by GAs. The predictor variables were the hourly average concentrations of carbon monoxide (CO), nitrogen oxide, nitrogen dioxide (NO(2)), and O(3) (recorded in the previous day at an urban site with traffic influence) and also meteorological data (hourly averages of temperature, solar radiation, relative humidity and wind speed). The study was performed for the period from May to August 2004. Several models were achieved and only the best model of each methodology was analysed. In threshold models, the variables selected by GAs to define the O(3) regimes were temperature, CO and NO(2) concentrations, due to their importance in O(3) chemistry in an urban atmosphere. In the prediction of O(3) concentrations, the threshold model that considers two regimes was the one that fitted the data most efficiently.

Photochemical Pollution Modeling of Ozone at Metropolitan Area of Porto Alegre - RS/Brazil using WRF/Chem

NASA Astrophysics Data System (ADS)

Cuchiara, G. C.; Carvalho, J.

2013-05-01

One of the main problems related to air pollution in urban areas is caused by photochemical oxidants, particularly troposphere ozone (O3), which is considered a harmful substance. The O3 precursors (carbon monoxide CO, nitrogen oxides NOx and hydrocarbons HCs) are predominantly of anthropogenic origin in these areas, and vehicles are the main emission sources. Due to the increased urbanization and industrial development in recent decades, air pollutant emissions have increased likewise, mainly by mobile sources in the highly urbanized and developed areas, such as the Metropolitan Area of Porto Alegre-RS (MAPA). According to legal regulations implemented in Brazil in 2005, which aimed at increasing the fraction of biofuels in the national energy matrix, 2% biodiesel were supposed to be added to the fuel mixture within three years, and up to 5% after eight years of implementation of these regulations. Our work performs an analysis of surface concentrations for O3, NOx, CO, and HCs through numerical simulations with WRF/Chem (Weather Research and Forecasting model with Chemistry). The model is validated against observational data obtained from the local urban air quality network for the period from January 5 to 9, 2009 (96 hours). One part of the study focused on the comparison of simulated meteorological variables, to observational data from two stations in MAPA. The results showed that the model simulates well the diurnal evolution of pressure and temperature at the surface, but is much less accurate for wind speed. Another part included the evaluation of model results of WRF/Chem for O3 versus observed data at air quality stations Esteio and Porto Alegre. Comparisons between simulated and observed O3 revealed that the model simulates well the evolution of the observed values, but on many occasions the model did not reproduce well the maximum and minimum concentrations. Finally, a preliminary quantitative sensitivity study on the impact of biofuel on the concentrations of O3 in RMPA was performed, revealing that there was little difference between a simulation using 0% and another one using 20% biodiesel.

A modelling exercise to examine variations of NOx concentrations on adjacent footpaths in a street canyon: The importance of accounting for wind conditions and fleet composition.

PubMed

Gallagher, J

2016-04-15

Personal measurement studies and modelling investigations are used to examine pollutant exposure for pedestrians in the urban environment: each presenting various strengths and weaknesses in relation to labour and equipment costs, a sufficient sampling period and the accuracy of results. This modelling exercise considers the potential benefits of modelling results over personal measurement studies and aims to demonstrate how variations in fleet composition affects exposure results (presented as mean concentrations along the centre of both footpaths) in different traffic scenarios. A model of Pearse Street in Dublin, Ireland was developed by combining a computational fluid dynamic (CFD) model and a semi-empirical equation to simulate pollutant dispersion in the street. Using local NOx concentrations, traffic and meteorological data from a two-week period in 2011, the model were validated and a good fit was presented. To explore the long-term variations in personal exposure due to variations in fleet composition, synthesised traffic data was used to compare short-term personal exposure data (over a two-week period) with the results for an extended one-year period. Personal exposure during the two-week period underestimated the one-year results by between 8% and 65% on adjacent footpaths. The findings demonstrate the potential for relative differences in pedestrian exposure to exist between the north and south footpaths due to changing wind conditions in both peak and off-peak traffic scenarios. This modelling approach may help overcome potential under- or over-estimations of concentrations in personal measurement studies on the footpaths. Further research aims to measure pollutant concentrations on adjacent footpaths in different traffic and wind conditions and to develop a simpler modelling system to identify pollutant hotspots on our city footpaths so that urban planners can implement improvement strategies to improve urban air quality. Copyright © 2016 Elsevier B.V. All rights reserved.

Comparative analysis of meteorological performance of coupled chemistry-meteorology models in the context of AQMEII phase 2

EPA Science Inventory

Air pollution simulations critically depend on the quality of the underlying meteorology. In phase 2 of the Air Quality Model Evaluation International Initiative (AQMEII-2), thirteen modeling groups from Europe and four groups from North America operating eight different regional...

The Impacts of Different Meteorology Data Sets on Nitrogen Fate and Transport in the SWAT Watershed Model

EPA Science Inventory

In this study, we investigated how different meteorology data sets impacts nitrogen fate and transport responses in the Soil and Water Assessment Tool (SWAT) model. We used two meteorology data sets: National Climatic Data Center (observed) and Mesoscale Model 5/Weather Research ...

U.S. Army Research Laboratory Meteorological Measurements for Joint Urban 2003

DTIC Science & Technology

2009-09-01

identical system operated by Arizona State University south to southeast of the CBD. The ARL Lidar system was set up atop a four-story parking garage ... Stereo Height and Motion Analysis: Applications, Fourth Winds Workshop, WMO, 1998. Chang, S. S.; Huynh, G. D.; Klipp, C. L.; Williamson, C. C

Urban boundary-layer height determination from lidar measurements over the paris area.

PubMed

Menut, L; Flamant, C; Pelon, J; Flamant, P H

1999-02-20

The Paris area is strongly urbanized and is exposed to atmospheric pollution events. To understand the chemical and physical processes that are taking place in this area it is necessary to describe correctly the atmospheric boundary-layer (ABL) dynamics and the ABL height evolution. During the winter of 1994-1995, within the framework of the Etude de la Couche Limite Atmosphérique en Agglomération Parisienne (ECLAP) experiment, the vertical structure of the ABL over Paris and its immediate suburbs was extensively documented by means of lidar measurements. We present methods suited for precise determination of the ABL structure's temporal evolution in a dynamic environment as complex as the Paris area. The purpose is to identify a method that can be used on a large set of lidar data. We compare commonly used methods that permit ABL height retrievals from backscatter lidar signals under different meteorological conditions. Incorrect tracking of the ABL depth's diurnal cycle caused by limitations in the methods is analyzed. The study uses four days of the ECLAP experiment characterized by different meteorological and synoptic conditions.

Integrated Meteorology and Chemistry Modeling: Evaluation and Research Needs

EPA Science Inventory

Over the past decade several online integrated atmospheric chemical-transport and meteorology modeling systems with varying levels of interactions among different atmospheric processes have been developed. A variety of approaches to meteorology-chemistry integration with differe...

Potential Risk Areas of Aedes albopictus in South-Eastern Iran: A Vector of Dengue Fever, Zika, and Chikungunya

PubMed Central

Nejati, Jalil; Bueno-Marí, Rubén; Collantes, Francisco; Hanafi-Bojd, Ahmad A.; Vatandoost, Hassan; Charrahy, Zabihollah; Tabatabaei, Seyed M.; Yaghoobi-Ershadi, Mohammad R.; Hasanzehi, Abdolghafar; Shirzadi, Mohammad R.; Moosa-Kazemi, Seyed H.; Sedaghat, Mohammad M.

2017-01-01

The possibility of the rapid and global spread of Zika, chikungunya, yellow fever, and dengue fever by Aedes albopictus is well documented and may be facilitated by changes in climate. To avert and manage health risks, climatic and topographic information can be used to model and forecast which areas may be most prone to the establishment of Ae. albopictus. We aimed to weigh and prioritize the predictive value of various meteorological and climatic variables on distributions of Ae. albopictus in south-eastern Iran using the Analytical Hierarchy Process. Out of eight factors used to predict the presence of Ae. albopictus, the highest weighted were land use, followed by temperature, altitude, and precipitation. The inconsistency of this analysis was 0.03 with no missing judgments. The areas predicted to be most at risk of Ae. albopictus-borne diseases were mapped using Geographic Information Systems and remote sensing data. Five-year (2011–2015) meteorological data was collected from 11 meteorological stations and other data was acquired from Landsat and Terra satellite images. Southernmost regions were at greatest risk of Ae. albopictus colonization as well as more urban sites connected by provincial roads. This is the first study in Iran to determine the regional probability of Ae. albopictus establishment. Monitoring and collection of Ae. albopictus from the environment confirmed our projections, though on-going field work is necessary to track the spread of this vector of life-threatening disease. PMID:28928720

CentNet—A deployable 100-station network for surface exchange research

NASA Astrophysics Data System (ADS)

Oncley, S.; Horst, T. W.; Semmer, S.; Militzer, J.; Maclean, G.; Knudson, K.

2014-12-01

Climate, air quality, atmospheric composition, surface hydrology, and ecological processes are directly affected by the Earth's surface. Complexity of this surface exists at multiple spatial scales, which complicates the understanding of these processes. NCAR/EOL currently provides a facility to the research community to make direct eddy-covariance flux observations to quantify surface-atmosphere interactions. However, just as model resolution has continued to increase, there is a need to increase the spatial density of flux measurements to capture the wide variety of scales that contribute to exchange processes close to the surface. NCAR/EOL now has developed the CentNet facility, that is envisioned to have on the order of 100 surface flux stations deployable for periods of months to years. Each station would measure standard meteorological variables, all components of the surface energy balance (including turbulence fluxes and radiation), atmospheric composition, and other quantities to characterize the surface. Thus, CentNet can support observational research in the biogeosciences, hydrology, urban meteorology, basic meteorology, and turbulence. CentNet has been designed to be adaptable to a wide variety of research problems while keeping operations manageable. Tower infrastructure has been designed to be lightweight, easily deployed, and with a minimal set-up footprint. CentNet uses sensor networks to increase spatial sampling at each station. The data system saves every sample on site to retain flexibility in data analysis. We welcome guidance on development and funding priorities as we build CentNet.

Relationship between Surface Urban Heat Island intensity and sensible heat flux retrieved from meteorological parameters observed by road weather stations in urban area

NASA Astrophysics Data System (ADS)

Gawuć, Lech

2017-04-01

Urban Heat Island (UHI) is a direct consequence of altered energy balance in urban areas (Oke 1982). There has been a significant effort put into an understanding of air temperature variability in urban areas and underlying mechanisms (Arnfield 2003, Grimmond 2006, Stewart 2011, Barlow 2014). However, studies that are concerned on surface temperature are less frequent. Therefore, Voogt & Oke (2003) proposed term "Surface Urban Heat Island (SUHI)", which is analogical to UHI and it is defined as a difference in land surface temperature (LST) between urban and rural areas. SUHI is a phenomenon that is not only concerned with high spatial variability, but also with high temporal variability (Weng and Fu 2014). In spite of the fact that satellite remote sensing techniques give a full spatial pattern over a vast area, such measurements are strictly limited to cloudless conditions during a satellite overpass (Sobrino et al., 2012). This significantly reduces the availability and applicability of satellite LST observations, especially over areas and seasons with high cloudiness occurrence. Also, the surface temperature is influenced by synoptic conditions (e.g., wind and humidity) (Gawuc & Struzewska 2016). Hence, utilising single observations is not sufficient to obtain a full image of spatiotemporal variability of urban LST and SUHI intensity (Gawuc & Struzewska 2016). One of the possible solutions would be a utilisation of time-series of LST data, which could be useful to monitor the UHI growth of individual cities and thus, to reveal the impact of urbanisation on local climate (Tran et al., 2006). The relationship between UHI and synoptic conditions have been summarised by Arnfield (2003). However, similar analyses conducted for urban LST and SUHI are lacking. We will present analyses of the relationship between time series of remotely-sensed LST and SUHI intensity and in-situ meteorological observations collected by road weather stations network, namely: road surface kinetic temperature, wind speed, air temperature, soil temperature at a depth of 30 cm, road surface condition, relative humidity. Also, as there are wind speed and temperature observations at different heights available, we will calculate sensible heat flux in order to relate it to the intensity of SUHI.

Impact of meteorology and energy structure on solvent extractable organic compounds of PM2.5 in Beijing, China.

PubMed

Feng, Jialiang; Chan, Chak K; Fang, Ming; Hu, Min; He, Lingyan; Tang, Xiaoyan

2005-11-01

Twenty-eight PM2.5 samples collected in Summer (July 2002) and Winter (November 2002) at two sites in Beijing, China were analyzed using GC/MS to investigate the impact of meteorology and coal burning on the solvent extractable organic compounds (SEOC). The characteristics and abundance of the n-alkanes, polycyclic aromatic hydrocarbons (PAHs), n-fatty acids and n-alkanols were determined. Source identification was made using organic species as molecular markers. Semi-volatile compounds of alkanes and PAHs had much higher concentrations in winter than summer because of the large difference in the temperature between the seasons. Plant wax emission was a major contributor to n-alkanes in summer, but fossil fuel residue was a major source (>80%) in winter. The seasonal differences in the distribution of pentacyclic triterpanes clearly shows the impact of coal burning for space heating in winter. The yield of PAHs in winter (148 ng m(-3) at the urban site and 277 ng m(-3) at the suburban site) was six to eight times higher than that in summer and was found to be mainly from coal burning. Higher pollutant concentrations were measured at the suburban site than the urban site in winter due to the rapid expansion of the city limit and the relocation of factories from urban to suburban areas over the last two decades.

Estimation of Secondary Compounds Concentrations Contributed by Biogenic VOC With Chemical Transport Model in the Central Area of Japan

NASA Astrophysics Data System (ADS)

Yamamoto, K.; Kanemaru, A.; Okumura, M.; Tohno, S.

2008-12-01

Biogenic VOC (BVOC) has comparably large contribution to generation of secondary air pollutants, such as photochemical oxidant or urban aerosol. In this study a BVOC emission inventory in the Kansai area, which is located in the central part of Japan, based on the field observation was developed. Some validations of the inventory were conducted by estimating the concentration distribution of oxidants with this developed and an existing BVOC emission inventory in Kansai area by meteorological model MM5 and atmospheric chemical transport model CMAQ. In the development of BVOC emission, the vegetation map by the Biodiversity Center of Japan which had been arranged as basic information on natural environmental preservation in a regional standard mesh (the third mesh) in 1999 was used. In this study isoprene and the mono-terpene were taken up as BVOC. Quercus crispula and Quercus serrata were selected as the source of isoprene, and Cryptomeria japonica, Chamaecyparis obtuse, Quercus phillyraeoides, Pinus densiflora, and Pinus thunbergii were selected as sources of mono-terpene. The parameter of the basic emission rate included in the model was decided by arranging the result of the observation in Kansai Research Center of Forestry and Forest Products Research Institute in each season. This emission flux from each species were calculated by G93 model by Guenther et al. and meteorological fields for the model, such as temperatures and sunlight intensities, were renewed hour by hour, therefore, this emission inventory has a high time resolution according to the season and time. In calculating meteorological fields, meteorological model MM5 Ver.3.7 was conducted in Japanese standard mesh in the selected five days of April, July, and October in 2004, and January 2005 respectively, and taking out the result of wind velocities and temperatures for substituting to the G93 model. Then atmospheric chemical transport model CMAQ Ver.4.6 with the emission inventories and meteorological fields was used for estimating secondary produced compounds concentration in the Kansai region. While the emission amount data of BVOC is also included in the EAGrid-Japan database, constructed by A. Kannari et al., another simulation with this existing BVOC emission inventory was conducted. As for other emission inventories of precursors, EAGrid-Japan was also used in both simulations. According to the result of estimation of BVOC emission, the total amount of BVOC is almost same as that of EAGrid-Japan, however, the ratio of isoprene to total BVOC emission is quite low in our estimation, due to the used vegetation map in this study, and the configuration of basic emission parameter in Autumn and Winter which is set to zero. According to the result of atmospheric chemical transport simulation with this developed BVOC inventory, oxidant concentrations are lower than observed values. This result suggests that the amount of isoprene emission strongly affected on the concentrations of oxidants, therefore, more accurate vegetation map data as a basis of BVOC emissions should be developed.

Outdoor environment, ozone, radionuclide-associated aerosols and incidences of infantile eczema in Minsk, Belarus.

PubMed

Belugina, I N; Yagovdik, N Z; Belugina, O S; Belugin, S N

2018-05-06

The early occurrence of atopic dermatitis in infants may be influenced by urban air pollution. The aim of this study was to determine the relationship between incidences of infantile eczema in children under 2 years of age and urban outdoor environmental factors. A 11-year population-based study was conducted in retrospective design. The age/gender-adjusted incidence rates of infantile eczema were determined using the data of outpatient visits. We analysed 1965 cases with atopic dermatitis including infantile eczema in relation to the annual means of outdoor monitoring data from 2005 through 2015 in Minsk. Logistic regression and principal component analysis were performed to determine association between the annual means of air pollutants, meteorological variables and incidences of infantile eczema. Higher mean annual carbon monoxide, ammonia, formaldehyde, lead, particulate matter and ground-level ozone were associated with high incidence rates of infantile eczema both in boys and girls. Higher nitrogen dioxide was associated with high incidence rates of infantile eczema in girls 1-2 years of age and boys 0-2 years of age. There were identified by principal component analysis five combinations of pollutants and meteorological factors. High incidence rates of infantile eczema were associated with the combinations contained higher levels of air pollutants and ultraviolet index, or lower β-activity of the radionuclide-associated aerosols. The higher phenol and formaldehyde levels the higher incidence rates of infantile eczema were observed among boys 0-1 years of age and girls 1-2 years of age. The higher total column ozone with lower lead level was associated with low incidence rates of infantile eczema among boys and girls 1-2 years of age. Urban outdoor air pollutants and their combination with meteorological conditions may impact onset of infantile eczema in both genders. © 2018 European Academy of Dermatology and Venereology.

Heavy haze episodes in Beijing during January 2013: Inorganic ion chemistry and source analysis using highly time-resolved measurements from an urban site.

PubMed

Han, Bin; Zhang, Rui; Yang, Wen; Bai, Zhipeng; Ma, Zhiqiang; Zhang, Wenjie

2016-02-15

The heavy air pollution that occurred in Beijing in January of 2013 attracted intense attention around the world. During this period, we conducted highly time-resolved measurements of inorganic ions associated with PM2.5 at an urban site of Beijing, and investigated ion chemistry and potential sources. Hourly concentrations of Cl(-), NO3(-), SO4(2-), Na(+), NH4(+), K(+), Mg(2+), and Ca(2+) were measured. Peak concentrations of SO4(2-) and NO3(-) were observed on the 10th-15th, 21st-24th, and the 26th-30th during this monitoring campaign. The percentages of SO4(2-) and NH4(+) in total ion concentration increased with the enhancement of PM2.5 concentrations, indicating that high concentrations of SO4(2-) and NH4(+) may play important roles in the formation of haze episodes. The ratio of [NO3(-)]/[SO4(2-)] was calculated, revealing that the sources of SO4(2-) would contribute more to the formation of PM2.5 than mobile sources. Diurnal variations of SO4(2-), NO3(-), NH4(+) (SNA) exhibited a similar pattern, with high concentrations at night and low levels during the day, revealing that meteorological conditions, such as mixing layer height, relative humidity, were likely to be responsible for high levels of SNA at night. The roles of meteorological conditions were further discussed in the formation of secondary inorganic ions. Relative humidity and temperature played key roles and exhibited positive correlations with secondary inorganic ions. An aerosol inorganics simulation model showed that SNA existed mainly in the aqueous phase during the sampling period. Furthermore, potential sources were identified by applying positive matrix factorization model. Secondary nitrate, secondary sulfate, coal combustion and biomass burning, as well as fugitive dust, were considered to be major contributors to total ions. Copyright © 2015. Published by Elsevier B.V.

First characterization and comparison of TEB model simulations with in situ measurements regarding radiation balance in a single urban canyon at the BOKU site (Vienna)

NASA Astrophysics Data System (ADS)

Oswald, Sandro; Trimmel, Heidelinde; Revesz, Michael; Nadeem, Imran; Masson, Valéry; Weihs, Philipp

2017-04-01

According to the World Health Organization more than half of the world population lives in a city since 2010. Predictions foresee that by 2030 six out of ten people will live in an urban area. As a result, many cities are expanding in size. Almost 10% of all urban dwellers live in megacities (defined according to UN HABITAT as a city with a population of more than 10 million). There are several effects in cities which strongly influence human health. Visible influences like the severe emissions of air pollutants by industry and traffic (e.g. Mayer H., 1999, Grimmond et al., 2010) are obvious to people but thermal stress in urban areas is only recently recognized for its strong devastating effect on human health. As a consequence, the urban environment virtually influences all weather parameters that have an impact on human comfort and thermal stress. Within this study, we investigate effects of city growth and the development of outlying districts on the local climate of Vienna. We focus particularly on the influence of urban heat island and consequent the risk for heat related illnesses or thermal stress for people. To quantify radiation balance and other important meteorological factors, we performed an extensive field campaign with three types of net radiometer in three different heights at BOKU site in August 2016. The first results indicated a strong correlation (ρ=0.96) between the Town Energy Balance (TEB) model and the measurements of the top net radiometer regarding radiation balance at roof level, meanwhile the TEB results are slightly underestimated. Further check if the measurements are reasonable, a comparison of the input values (global and direct solar radiation) for the TEB simulation with Secondary Standard measurements of ARAD site Wien Hohe Warte shows a deviation under 2% concerning interquartile range on clear sky days. The next steps will enclose TEB simulations, coupled with the mesoscale Weather Research and Forecasting (WRF) model, for whole Vienna including outlying districts and will quantify a possible future urban climate scenario until 2030. References: Grimmond C.S.B., et al.: Climate and More Sustainable Cities: Climate Information for Improved Planning and Management of Cities (Producers/Capabilities Perspective). Procedia Environmental Sciences 1, 247-274, 2010. Mayer H.: Air pollution in cities. Atmospheric Environment, 33, 4029 - 4037, 1999.

Identifying and monitoring urban heat island in Bucharest using satellite time series and low cost meteorological sensors

NASA Astrophysics Data System (ADS)

Sandric, Ionut; Onose, Diana; Vanau, Gabriel; Ioja, Cristian

2016-04-01

The present study is focusing on the identification of urban heat island in Bucharest using both remote sensing products and low cost temperature sensors. The urban heat island in Bucharest was analyzed through a network of sensors located in 56 points (47 inside the administrative boundary of the city, 9 outside) 2009-2011. The network lost progressively its initial density, but was reformed during a new phase, 2013-2015. Time series satellite images from MODIS were intersected with the sensors for both phases. Statistical analysis were conducted to identify the temporal and spatial pattern of extreme temperatures in Bucharest. Several environmental factors like albedou, presence and absence of vegetation were used to fit a regression model between MODIS satellite products sensors in order to upscale the temperatures values recorded by MODIS For Bucharest, an important role for air temperature values in urban environments proved to have the local environmental conditions that leads to differences in air temperature at Bucharest city scale between 3-5 °C (both in the summer and in the winter). The UHI maps shows a good correlation with the presence of green areas. Differences in air temperature between higher tree density areas and isolated trees can reach much higher values, averages over 24 h periods still are in the 3-5 °C range The results have been obtained within the project UCLIMESA (Urban Heat Island Monitoring under Present and Future Climate), ongoing between 2013 and 2015 in the framework of the Programme for Research-DevelopmentInnovation for Space Technology and Advanced Research (STAR), administrated by the Romanian Space Agency Keywords: time series, urban heat island